Post on 19-Apr-2022
Market Basket Analysis of Ingredients and Flavor Products
by Yuhan Wang
A THESIS
submitted to
Oregon State University
Honors College
in partial fulfillment of the requirements for the
degree of
Honors Baccalaureate of Science in Business Information System (Honors Associate)
Presented August 31, 2016 Commencement June 2017
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AN ABSTRACT OF THE THESIS OF
Yuhan Wang for the degree of Honors Baccalaureate of Science in Business Information System presented on August 31, 2016. Title: Market Basket Analysis of Ingredients and Flavor Products
Abstract approved:_____________________________________________________
Bin Zhu
In today, information plays a more and more important role in business world.
The companies are full of data, but poor of valuable information extracted from that
diverse data. Data mining, as a process of transferring data from variety perspectives
to useful information, is the new trend for businesses. It can be used to make more
targeted business model or strategies decisions.
Market basket analysis is one of the most useful modeling techniques in data
mining. It usually used to analyze customer purchases behaviors. The results can
provide decision-makers more valuable information such as marketing strategies
making, inventory controlling, and cross sales.
The main objective of this thesis is to study how 15 flavor products sold by
Zengcheng Handyware Seasoning Company in five different regions interrelate. And
based on the correlation results, how to provide valuable information to improve
company’s marketing activities.
Key Words: data mining, market basket analysis, association rules Corresponding e-mail address: jasminewang417@gmail.com
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©Copyright by Yuhan Wang August 31, 2016
All Rights Reserved
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Table of Content Chapter 1: Introduction ............................................................................................. 7
1.1 Overview ..................................................................................................................................... 7
1.2 Research Problem Description ................................................................................................. 7
Chapter 2: Data ........................................................................................................... 9
2.1 Data Description .................................................................................................................... 9
2.1.1 Basic description ............................................................................................................... 9
2.1.2 Description of regions ....................................................................................................... 9
2.1.3 Description of dataset ..................................................................................................... 11
2.2 Dataset Adjustment ............................................................................................................. 12
2.3 Considerations and Assumptions ....................................................................................... 13
2.4 Research Questions ............................................................................................................. 14
Chapter 3: Research Methodology .......................................................................... 15
3.1 Market Basket Analysis .......................................................................................................... 15
3.2 Association Rule ...................................................................................................................... 15
3.2.1 Definition of Association Rule......................................................................................... 15
3.2.2 Process of Association Rule ............................................................................................. 18
3.2.3 Frequent Set of Items Generation .................................................................................. 18
3.2.4 Association Rules Generation ......................................................................................... 22
Chapter 4: Data analysis and results ...................................................................... 24
4.1 Market Basket Analysis .......................................................................................................... 24
4.1.1 Analysis Package Selection -- SPSS ................................................................................ 24
4.1.2 SPSS Modeling Process ................................................................................................... 25
4.2 Results .......................................................................................................................................... 28
4.2.1 Result for All Regions ...................................................................................................... 28
4.2.2 Result for the North China Region ................................................................................. 32
4.2.3 Result for the South China Region ................................................................................. 36
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4.2.4 Result for the Mid China Region .................................................................................... 39
4.2.5 Result for the East China Region ................................................................................... 43
4.2.6 Result for the South West China Region ....................................................................... 46
Chapter 5: Conclusions ............................................................................................ 50
5.1 General Discussion .................................................................................................................. 50
5.2 Academic Contribution .......................................................................................................... 50
5.3 Business Contribution ............................................................................................................ 51
5.4 Limitations of the study .......................................................................................................... 51
5.5 Directions for Future Research ............................................................................................. 52
Bibliography .............................................................................................................. 53
Appendices ................................................................................................................. 54
Appendix A: Data Description ..................................................................................................... 54
Appendix B: Results ..................................................................................................................... 58
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Chapter 1: Introduction 1.1 Overview
Today, we live in the age of information. More and more data from multiply
dimensions are surrounding us. For the companies, the age of information provide
them an opportunity to collect enormous amounts of data. In order to transfer the data
into information, data mining become more and more popular in business world.
Data mining usually starts from data collection. And clients are the source of
data collection. Every purchasing transaction includes multi-angles data about clients.
By analyzing and summarizing the large number of data, it is easy to extract useful
information from raw data. The hidden patterns or models can be found also. The
valuable information includes hidden patterns can be used in multiply business
activities such as increase profit, decrease cost, and making market strategies.
There are various statistical algorithms in data mining. For instance,
classification, clustering, regression, artificial intelligence, neural networks, decision
trees, and association rules are all important data mining techniques to study
knowledge from data (Ramageri). In this study, we decided to use association rules,
which also called market basket analysis, to mining the provided dataset.
As a data mining technique, market basket analysis always focuses on “what
goes with what”. It can provide the researcher more information than just the products
in the “shopping cart”. In this research, market basket analysis method can help us to
study the relationship between different flavor products purchases in different regions.
Then, the deeper analysis results can provide the company more useful marketing
strategy recommendations and guides for any specific region.
1.2 Research Problem Description In the past decades, market basket analysis usually appealed in retail market
or e-commerce market. However, the advanced technology makes not only retailers
have the opportunity to collect customers’ data, manufacturer can also gather their
clients’ information to provide high quality products and technical support.
Companies in multiple industries can use market basket analysis to help their
decision-making. This technique can help the business to eliminate the blind market
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and know more about their customers. By applying market basket analysis, we can
find valuable information about customers, and hidden connection between products
that help decision-makers to do further strategy making.
The main objective of this thesis is finding out how to create or improve
recommendation of flavor products to customers in different regions based on their
shopping behaviors. Mining association rules based on analyzing transaction-based
dataset can provide us useful information about co-purchases products. Classified the
dataset by regions will help us to figure out the product preferences in different
regions.
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Chapter 2: Data 2.1 Data Description
2.1.1 Basic description The dataset used in this study is a collection of 15 different flavor products’
sales records from 2013 to 2015. The study is based on this simulated dataset
provided by Zengcheng Handyware Seasoning Company. The simulated dataset still
follows the original dataset’s trend and characteristics. The sales records were
classified by both year and region. In the dataset, there are five main regions: the
South China Region, the North China Region, the Mid China Region, the East China
Region, and the South West China Region.
2.1.2 Description of regions There is an obvious distance between the South China Region and the other
four regions. And the sales volume for the South West China Region is only half of
the South China Region. See Table 2.1 for more detailed information.
Table 2.1 Regional Monthly Sales (kg) Comparison
South
China
North
China
Mid
China
East
China
South West
China
Jan. 43270.00 26500.33 25019.33 30633.67 23089.67
Feb. 20637.67 10923.00 13426.33 13542.00 11363.00
Mar. 38186.67 24626.67 23568.00 27279.33 21145.00
Apr. 35506.67 24187.33 22812.00 25886.67 19758.33
May. 38698.33 22212.67 20531.67 27705.67 15933.67
Jun. 32966.33 22851.00 20334.67 26991.33 19392.33
Jul. 47471.33 29238.33 24165.67 29502.00 20293.67
Aug. 55559.00 29363.67 29857.33 32669.67 23031.33
Sep. 62206.33 34186.00 29722.00 38224.00 29586.00
Oct. 47238.67 22657.33 22453.33 29942.67 16073.67
Nov. 59163.00 27041.00 25675.67 28846.67 19397.33
Dec. 56090.67 33801.67 28716.00 30300.33 23652.67
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The average monthly sales volume for different regions also showed us the
aggressiveness of the South China Region. This region’s monthly average sales
volume is the double of the South West Region, which is the weakest during the past
three years. See Table 2.2 for more detailed statistics.
Table 2.2 Regional Sales Comparison
Average Sales
per month
(kg)
Average
Monthly Sales
in 2013 (kg)
Average
Monthly Sales
in 2014 (kg)
Average
Monthly Sales
in 2015 (kg)
South 44,749.56 39,591.50 42,350.17 52,307.00
North 25,632.42 24,102.17 23,889.67 28,905.42
Mid 23,856.83 20,150.50 22,078.08 29,341.92
East 28,460.33 28,556.83 29,613.67 27,210.50
South West 20,226.39 18,443.00 19,870.00 22,366.17
The fluctuations of the company’s total monthly sales from 2013 to 2015 are
stable. The sales volume always starts from the lowest February then increase to the
first high value at March. After fluctuating smoothly from March to June, it increases
to the peak on September substantially. From September to next February, the sales
volume usually fluctuates smoothly. In 2013 to 2015, peaks are located at the end of
the summer (August or September), and the lowest point happens in February.
The reason why both of February and October have lower monthly sale is
related to nationwide holiday. In February, there is a 15 days break nationwide in
China to celebrate spring festival. And in October, there is a 7 days nationality
holiday. During the holiday, there are no orders and productions. Therefore, both of
these two months usually have a lower sales than other months.
The peak happened in August related to summer break schedule. In China, all
of the primary schools, middle schools, high schools, and universities have the
summer break during July to September. As the main purchasing power, students will
consume more snacks products during the summer break. So during August, the sales
usually goes well. Another peak in November represents that manufacturers are all
preparing for the spring festival. Every year, the snacks consumption during spring
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festival is very high. Therefore, November usually is another high point during the
year. Figure 2.1 Regional Monthly Sales
2.1.3 Description of dataset The raw dataset is classified by region. All five regions’ sales records have
been listed. The transaction database consists of the following five elements:
• Product name – name of the products sold in all regions. Abbreviation
descriptions are listed. (Table 1, appendix A)
• Month – month of information collected
• Year – year of information collected
• Region – the name of the five different regions
• Sales volume – the sales volume in kilogram
This dataset includes 15 products, which sold in five regions. Some products,
such as Tomato Flavor and Crab Flavor, have the greater volume of sales than other
flavors since they have a wider market acceptance. Most end products includes these
flavors. Some products’ sales, such as Chives flavor or Hot & Spice Sichuan Flavor
are much lower than the average monthly sales because of the small client base.
These kind of products are currently not mainstream product in the market. They are
only accepted by a small group of customers. Hence, there is a big sales gap between
popular products and niche products. For instance, the most popular product, Tomato
Flavor, has a ten times average monthly sales than the Hot & Spice Sichuan Flavor.
0
20000
40000
60000
80000
Jan. Feb. Mar. Apr. May. Jun. Jul. Aug. Sep. Oct. Nov. Dec.
KILO
GRAM
2013 -‐ 2015 Regional Monthly Sales
2013 2014 2015
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And most products’ average monthly sales are lower than the average number. Table
2.3 provides more detailed information.
Table 2.3
Product Name Average number of
unique items per
month
Difference with
Total Average Sales
Tomato Flavor 8462.61 6556.93
Crab Flavor 5406.44 3500.77
Sauced Beef Flavor 1726.86 -178.81
Cheese Corn Flavor 1632.90 -272.77
Barbecue Flavor 1617.11 -288.56
Pepper Beef Steak Flavor 1395.00 -510.67
Chicken Flavor 1203.71 -701.96
Curry Barbecue Flavor 1168.66 -737.01
Cumin Barbecue Flavor 1160.65 -745.02
Hot & Spicy Salt Flavor 959.89 -945.78
Pork Steak Flavor 920.27 -985.41
Yolk Flavor 902.23 -1003.44
Kimchi Flavor 541.23 -1364.45
Chives Flavor 592.36 -1313.31
Hot & Spicy Sichuan Flavor 895.18 -1010.50
2.2 Dataset Adjustment One of the crucial points of the Market Basket Analysis is studying how a
product cross sell to customers. In another words, researcher usually more focused on
what kind of product that customers purchased instead of how many they purchased.
Therefore, depending on the research questions, the raw dataset should be adjusted
from the original sales-based to a true or false dataset.
A true or false dataset should only include the information about whether do
customers purchase the products or not. In usual, “1” is used to represent true, which
the customer purchases this specific product, and “0” means false, which the
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customer does not purchase it. In order to adjust the dataset, we decided to find a cut-
off point to differentiate the data between “1” and “0”.
In the given dataset, the certain differences in products’ sales volume were too
large to be ignored. We cannot use one fix number as the cut-off point for all products.
What’s more, since the provided dataset is simulate, there may also has inevitable
bias during the simulation process.
In order to avoid the bias and decrease the simulation error, we decided to use
the mean as the cut-off point. For the dataset includes all sales records in five regions,
the cut-off point for every product is the average monthly sales volume in all regions
for each product. For the dataset only includes specified region, the cut-off point for
every product is the average monthly sales volume in specified region. If the monthly
sales is higher than the cut-off point, it was marked as “1”, if lower, then “0”.
The adjusted datasets are available (see Appendix A, Table 2).
2.3 Considerations and Assumptions 1. Sales Record
The given dataset represents the 15 products’ monthly sales in five regions
from 2013 to 2015. However, since the Market Basket Analysis requires the
transaction-based dataset, we decide to treat one region’s one-month sales record
as one transaction.
2. Language
The initial dataset is in Mandarin. So the names of all products have been
translated to English (See Appendix A, Table 1).
3. Simulation
The given dataset is not the real sales records. All of the data have been
simulated for confidentiality purpose. But the simulated datasets keep the main
original trend and characteristics. Bias may exist because of the uncertainty of
simulation.
4. Correlation
A general assumption in this study is that sales of different products are
correlated.
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2.4 Research Questions Regional-oriented Research Questions: 1. What kinds of product are frequently purchased together in all five regions?
2. What kinds of product are frequently purchased together in South China Region?
3. What kinds of product are frequently purchased together in North China Region?
4. What kinds of product are frequently purchased together in Mid China Region?
5. What kinds of product are frequently purchased together in East China Region?
6. What kinds of product are frequently purchased together in South West China
Region?
15 products sold in all five regions will be analyzed for finding co-purchases
in different regions. This regional-oriented analysis will provide the company with
valuable information in further marketing strategies setting.
The Association Rule Analysis as the outcome of the Market Basket Analysis
is used to finding the frequent purchasing pattern, correlation and associations based
on the given dataset (Tan, Steinbach and Kumar). It can help us to mine the given
dataset and do recommendations.
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Chapter 3: Research Methodology
3.1 Market Basket Analysis Based on the given dataset, market basket analysis (MBA) is a perfect method
for this study. The raw data provided by Zengcheng Handyware Seasoning Company
does not have a good pointing. As an undirected data mining technique, market
basket analysis is a good start for knowing the large-scale of dataset (Padoe).
What’s more, there are three levels of market basket data: Customers, Orders,
and Items (Padoe). After observing the dataset, we know this dataset is transaction-
based and items-oriented. It includes five main customers (regions), 180 orders
(transactions), and 15 items (flavor products). All requirements for market basket
analysis are satisfied.
However, the main problem of this study is determining the right cut-off point
during the data adjustment. Using each product’s sales mean as the cut-off point may
generate the error. The uncertain error may affect results. Hence, the possible solution
is using different cut-off points to get the results. Then comparing the results to see
whether the error affect the final conclusions.
3.2 Association Rule As the outcome of the market basket analysis, association rule is a useful data
mining method for mining “frequent patterns, associations, correlations, or causal
structures among sets of items in transaction databases” (Han and Kamber). The
main idea of this technique is producing rules on associations between products from
a transaction-based dataset.
3.2.1 Definition of Association Rule According to the textbooks, Data Mining: Concepts and Techniques written
by Jiawei Han and KAmber Micheline, and Introduction to Data Mining written by
Pangning Tan, Steinbach Michael and Kumar Vipin, We can define the association
rule by the following steps.
Let I = {i1, i2, … , im} be a collection of m items in the market basket data.
Let T= {t1, t2, … , tn} be the set of all transactions in the market basket data.
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Each transaction ti contains a subset of items from I.
A transaction ti is said to contain an X, which is a collection of items, if X is a
subset of ti (X ⊆ ti , ti ∈ T).
An association rule is an implication expression of the form X à Y.
X and Y are disjoint collection of items (X ≠ ∅, Y ≠ ∅, X ∩ Y = ∅).
The main idea of association rule is finding the relationship between
purchases of different products. It can be represented as:
IF {purchase A & B (A, B ∈ X)} THEN {purchase C (C ∈ Y)}
X is an antecedent. Y is a Consequent.
So we can get:
Antecedent à Consequent [support, confidence]
The strength of an association rule is measured by support and confidence.
Support is the percentage of transactions that include both the antecedent and
the consequent. It determines how often a rule is applicable to the given dataset. If P
means probability, that
Support (X à Y) = P (X � Y)
Table 3.1 Example of Support
ID Items Support Calculus
1 A, B, C Total Support = 5
{AB}: 2; Support {AB} = 2/5 = 40%
{AC}: 2; Support {AC} = 2/5 = 40%
{BC}: 3; Support {BC} = 3/5 = 60%
{ABC}: 1; Support {ABC} = 1/5 = 20%
2 A, B, D
3 A, C
4 B, C
5 B, C, D
Confidence is the percentage of antecedent transactions that also have the
consequent item collection. It determines how frequently items in consequent (Y)
appear in the transactions, which contain the antecedent (X). If P means probability,
that
Confidence (X à Y) = P (Y | X)
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Table 3.2 Example of Confidence
ID Items Confidence Calculus
1 A, B, C
Confidence {AàB} = {AB}/{A} = 2/3 = 66%
Confidence {BàC} = {BC}/{B} = 3/4 = 75%
Confidence {CàD} = {CD}/{C} = 1/4 = 25%
Confidence {ABàC} = {ABC}/{AB} = 1/2=50%
2 A, B, D
3 A, C
4 B, C
5 B, C, D
Both of the support and confidence are very important in association rule. As
the measures of interestingness, “they respectively reflect the usefulness and certainty
of discovered rules” (Han and Kamber). A low support percentage means there is a
low probability the chosen items were purchased X and Y together. And a low
confidence percentage means there is a low percentage of customers who purchased
X will also bought Y. Therefore, both a minimum support threshold and a minimum
confidence threshold are necessary for this study. We want to find all rules XàY that
satisfied the following two criteria:
• The percentage of X and Y both appear must equal or higher than the
percentage of minimum support threshold of all given transactions.
• The percentage of Y appears in the given transaction that contain X must
equal or higher than the percentage of minimum condition threshold.
The performance of an association rule is measured by lift.
Lift is one of the correlation measures. The occurrence of the set of items, X,
is independent of the occurrence of Y if P (X � Y) = P (X) P (Y); otherwise, X and Y
are dependent and correlated. That is
𝐋𝐢𝐟𝐭 𝐗,𝐘 =𝐂𝐨𝐧𝐟𝐢𝐝𝐞𝐧𝐜𝐞 (𝐀 𝐁)
𝐒𝐮𝐩𝐩𝐨𝐫𝐭(𝐁) =𝐏 (𝐗 ∪ 𝐘)𝐏 𝐗 𝐏(𝐘)
If the value of lift is greater than 1, it indicates a rule that is useful in finding
consequent set of items. In another words, the occurrence of X and Y are positively
correlated. If the value of lift is less than 1, it means X is negatively correlated with Y.
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If the value of life is equal to 1, it means no correlation between X and Y. Computing
the lift is more useful than only selecting transactions randomly.
3.2.2 Process of Association Rule In general, there is a two-step process to solve the association rule problem
(Han and Kamber).
1. Generating Frequent Set of Items
Setting a minimum support threshold based on the given dataset. Then
generating all sets of items from the given dataset that satisfied the support
exceeds the minimum support threshold.
2. Generating Association Rules
Setting a minimum condition threshold based on the given dataset. Then
generating all sets of items from the frequent set of items that satisfied the
condition exceeds the minimum condition threshold.
3.2.3 Frequent Set of Items Generation This first step in association rule generation is finding all sets of items that
have high support (equal or higher than the minimum support threshold). A lattice
structure usually used to list all possible sets of items. Figure 3.1 shows us the
structure of 5 items (I = {a, b, c, d, e}). Therefore, if a given dataset includes 5 items,
there are 25 possible candidate sets of items and 1 null set of item. Therefore, for a 5
items dataset, there are 25 -1 frequent sets of items.
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Figure 3.1 Itemset Lattice for Five Products (Tan, Steinbach and Kumar)
In general, if the given dataset has k sets of items, there will be 2k -1 frequent
sets of items. Since number of sets of items (k) can be very large, the number of
frequent sets of items, 2k -1, will increase exponentially. In another word, the level of
complication is also exponentially growing (Tan, Steinbach and Kumar).
What’s more, if we want to determine the support count for all candidate sets
of items in the lattice structure, the brute-force approach is one of the essential
technologies for us. According to this method, we need to compare each candidate
frequent set of items against every transaction. Figure 3.2 shows the whole operations.
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Figure 3.2 Brute-‐force Approach Operations (Tan, Steinbach and Kumar)
As a very detailed and straightforward method, brute-force approach can help
us to find the best combinations in most situations. It is also a simple approach.
However, just like we mentioned before, the increasing number of itemsets will
complicates the computation exponentially. Therefore, brute-force approach is only
good for the study with a small scale of dataset.
When we have a large scale of dataset, we always prefer the Apriori
Algorithm approach. “Apriori is the first association rule mining algorithm that
pioneered the use of support-based pruning to systematically control the exponential
growth of candidate itemsets” (Tan, Steinbach and Kumar). It is a better method to
lower the computation’s level of complex. The operations of aprior algorithm
approach are showed as following:
Table 3.3 Original Sample Data
Minimum Support Count = 3
Transaction ID Items
1 {A, B, C, D}
2 {A, B, C, E}
3 {A, B, D}
4 {B, D}
5 {A, B, B}
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Table 3.4 Candidate 1-itemsets
Step 1: Count the number of transactions
for each item. (Note: even product B is
bought 6 times, it only occurs in 5
transactions)
Table 3.5 Candidate 1-itemsets-cont
Step 2: Discard the candidate itemsets if
the number of transactions is fewer than
minimum support count.
Table 3.6 Candidate 2-itemsets
Step 3: Make pairs of all products in table
4.5. Then count the number of purchases
for each pair.
Table 3.7 Candidate 2-itemsets-cont
Step 4: Repeat the step 2.
Table 3.8 Candidate 3-itemsets
Step 5: Repeat step 3 and step 4.
Item No. of transaction
A 4
B 5
C 2
D 3
E 1
Item No. of transaction
A 4
B 5
D 3
Itemset No. of transaction
AB 4
AD 2
BD 3
Itemset No. of transaction
AB 4
BD 3
Itemset No. of transaction
ABD 2
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The example above shows how the apriori algorithm approach controls the
exponentially growing in the number of candidate itemsets. The explanation of apriori
property shows us, “all subsets of a frequent item-set must also be frequent” (Tan,
Steinbach and Kumar).
If we already know an itemset is infrequent, there is no need to study its
subsets because they are also infrequent. Therefore, the apriori algorithm approach is
more efficient than the brute-force approach for large-scale of dataset in frequent
itemsets mining.
3.2.4 Association Rules Generation The second step in association rule generation is generating the exact
association rules based on the given frequent itemsets (Han and Kamber).
Each frequent itemset, Y, can produce up to 2k – 2 association rules. An
association rule can be extracted by partitioning the itemset Y into two non-empty
subsets, X and Y – X, such that X à Y – X satisfies the confidence threshold (Tan,
Steinbach and Kumar; Han and Kamber).
For instance, if X= {A, B, C}, it can produce up to 23 – 2 = 6 association rules.
All possible association rules are listed:
{A} à {B, C}
{B} à {A. C}
{C} à {A, B}
{A, B} à {C}
{A. C} à {B}
{B, C} à {A}
Apriori Algorithm can also be used in association rules generation. As a level-
wise approach, “each level corresponds to the number of items that belong to the rule
consequent” (Pang-Ning, 2006). The high-confidence rules are used to generate the
new rules by merging or discarding.
For instance, if we set {A, B, C} à {D} and {A, B, D} à {C} are high-
confidence rules, then the new rules can be generated by merging: {A, B} à {D, C}.
If we set {B, C, D} à {A} is a low-confidence rule, then all the rules includes {A}
can be discarded.
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Figure 3.3 Apriori Algorithm Rule Generation (Lanzi, 2009)
The graph above visualized shows what happens after apriori
algorithm detect the unsatisfied rules by correlations. If one rule is determined
to useless, then all the other included rules will be also determined useless
without any calculation needed. That can directly save time during the large-
scale of dataset analysis.
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Chapter 4: Data analysis and results
4.1 Market Basket Analysis Market basket analysis allows researchers to know more about the customer
behaviors and the sales pattern by analyzing the historical transactions. The basic data
adjustment has been completed in Excel.
For the frequent itemsets generating and association rules generating
procedures, we will use the apriori algorithm method by the selected analysis package.
And the minimum support will be set as 10%, the minimum confidence will be set as
80%, the minimum lift will be set as 1.
4.1.1 Analysis Package Selection -- SPSS There are several software can be used in data analysis research. For instance,
SPSS, R, SAS, Excel and Matlab are all good packages for data analysis. All of them
have their own advantages in analysis. The table 4.1 shows more detailed
comparative information (Connor)
Table 4.1 Comparison of data analysis software
Name Advantages Limitations Open Source
SPSS Large datasets
Visualization
Statistical analysis
Expensive No
R Library Support
Statistical analysis
Programming-oriented
Improper learning curve
Yes
Excel Easy to use
Complete function
Poor performance in large
datasets
No
Matlab Elegant Matrix
Support
Programming-oriented
Poor statistical ability
No
Based on that, we know SPSS is our best choice in this study. Although Excel
is an easy and full function package for data analysis, we cannot choose it since its
poor performance in large dataset. For the other two packages, R and Matlab, we
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have to give up them because of their weak visualization and programming-oriented
characteristics.
As a predictive analytics software, SPSS has the abilities in data collection,
statistics, modeling and deployment (IBM). It can not only build predictive models
based on the data collection, but also provide detailed statistical analysis visualized.
Therefore, for this study, we decided to use SPSS to determine what kinds of flavor
products will be purchased together in the specified region.
4.1.2 SPSS Modeling Process The following figures show how to build an association rules algorithm in
SPSS. All six-research questions mentioned in preview chapter can be answered by
loading different classified datasets into this model.
Figure 4.2 SPSS Modeling Explanation 1
Step 1: Load the Excel source.
Step 2: Assign a “Type” to the loaded Excel source.
Changing all roles of product to “Both”, which means the roles of the fields
are both input (predictor) and target (predicted). Then changing all products’
measurement level to “Flag” since we are using “0” and “1” in data.
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Figure 4.3 SPSS Modeling Explanation 2
Step 3: Add an “Apriori” model to the Type.
Setting the minimum antecedent support to 10%, the minimum rule
confidence to 80% and the maximum number of antecedents to 2 (products). The
reason why we control the maximum number of antecedents to two is limiting the
number of generated rules. If we allow more antecedents, more rules will be
generated. That will increase the difficulty level of mining rules.
Step 4: Run the Apriori Node Model to get the results.
The results includes all rules satisfied 10% minimum support and 80%
maximum confidence. We can sort the list by either support or confidence to do
further analysis.
27
Figure 4.4 SPSS Modeling Explanation 3
Step 5: Generate the rule sets based on the results.
Set the target field as each product, minimum support as 10%, minimum
confidence as 90%, and default value as 0. Then we will get the scoring of
association rules. Setting the minimum confidence as 90% when we generating
ruleset can decrease the difficulty of mining rulesets. Since we don’t need to analyze
all rules, only the rules have high confidence need to be focused. A higher minimum
confidence setting can help us more focus on the valuable rules.
What’s more, we can also use Association Rules Node to generate rules. The
steps are same as the Apriori Node.
28
4.2 Results
4.2.1 Result for All Regions Figure 4.6 Levels of Link between Two Products
Figure 4.6 gives us a graphical understanding about levels of products links.
The heavier line it shows, the stronger links. It provides us some one-to-one
relationships between products. Some strong links such as Chives Flavor and Sauced
Beef Flavor, Crab Flavor and Cheese Corn Flavor, Chives Flavor and Yolk Flavor
are visualized in this figure.
Table 4.2 Rule Statistics in all regions
Measurements Minimum Maximum Mean Stand.
Deviation
Condition Support 10.59 % 55.29% 29.04% 8.76%
Confidence 80.00% 100.00% 88.55% 5.35%
Rule Support 10.00% 48.82% 25.58% 7.42%
Lift 1.45 2.89 1.82 0.24
Deployability 0.00% 9.41% 3.47% 2.09%
Number of Rules: 365
29
Table 4.3 Information for Most Frequent Items
Item Name Records (%) Conditions (%) Predictions (%)
Curry beef 55.29 13.7 12.05
Sauced beef flavor 54.12 14.79 14.25
Pepper beef steak 54.12 13.7 8.49
Hot & spices salt 51.18 12.05 0.82
Chicken flavor 50.59 12.33 11.51
BBQ flavor 50 13.15 12.88
Cumin BBQ 47.06 15.62 13.42
Kimchi flavor 45.88 18.36 9.32
Tomato flavor 44.12 3.56 0.82
Yolk 44.12 13.15 5.75
Hot&spice sichuan 43.53 14.25 2.19
Cheese corn flavor 41.18 3.29 1.64
Pork steak 37.65 19.45 4.93
Chives flavor 31.76 21.37 1.64
Crab flavor 30.59 3.29 0.27
Table 4.2 shows us the rule statistics about the rules. It gives us a basic
understanding of the generated rules. There are 365 rules were generated, so we need
to do the scoring to find out the most valuable or interesting rules.
Table 4.3 provides us what products are popular in the original dataset, and
what products will be popular in future based on the prediction. For instance, Curry
Beef Flavor exists in 55.29% records. It is the most popular flavor based on the
original dataset. What’s more, Sauced Beef Flavor has the highest prediction
percentage, which means 14.25% rules include this flavor. In another word, Sauced
Beef Flavor may be the most popular product in future. Therefore, the company
should more focused on these high prediction products by promoting to increase the
sales or inventory and production cycling time control. We will also more focused on
analyzing the rules include these products. It is also a strong evidence for the
following valuable rules generation.
30
Table 4.4 Most Interesting Association Rules for All Regions (2013 – 2015)
Probability (%) Antecedent Consequent
Rule 1 1 Chives Flavor and Pepper Beef
Steak
Sauced beef flavor
Rule 2 0.909 Cheese Corn Flavor and
Chives Flavor
Yolk flavor
Rule 3 0.917 Chives Flavor and Hot Spice
Sichuan
BBQ flavor
Rule 4 0.963 Pork Steak Flavor and Hot
Spice Salt
Curry beef flavor
Rule 5 1 Cheese Corn and Pepper Beef
Steak
Curry beef flavor
Rule 6 0.958 Crab Flavor and BBQ Flavor Cheese corn flavor
Rule 7 0.955 Crab Flavor and Sauced Beef
Flavor
Cheese corn flavor
Rule 8 0.912 Chives Flavor and Pepper Beef
Steak
Curry beef flavor
Rule 9 1 Chives Flavor and Hot Spice
Sichuan
Pork Steak flavor
Rule 10 0.923 Yolk and Cheese Corn Flavor BBQ flavor
Table 4.4 shows us the “most interesting” association rules based on analyzing
the dataset for all regions. The result were scored based the rule sets generation by
targeting each product. (Full result is available in Appendix B, Table 1.)
Choosing the rules with high confidence, high lift, but low support. A rule
satisfied all three conditions usually means the products do not have a high
appearance rate in dataset, but they are associated with each other. In another word,
this rule is unpredictable in previous research. Then, picking up the highest
probability rules related to those high prediction products. The full results of rule sets
generation and scoring are available in Appendix B, Table 2. And the detailed
31
transaction and scoring information in tabular format for top ten rules is also available
in Appendix B, Table 3.
High affinity products:
1. If a customer purchases Crab Flavor and BBQ Flavor at the same time,
there is 95.8% probability that the customer will order Cheese Corn
Flavor.
As one of the most popular flavor in snacks market, BBQ Flavor
already has a lot of mature products nationwide for a long time. What’s more,
in the past three years, Crab Flavor becomes more and more popular in the
nuts and beans end product market. And this flavor gradually expands to other
kinds of end product such as chips or crackers. Both of these two flavors have
good trends in crackers market. Cheese Corn Flavor, as a western taste flavor
usually used in snacks and crackers products, it is highly accepted among
young end product customers in recent years. For the customers who target
the snacks and crackers market, they do have a high probability to purchase all
these three flavors at the same time. Therefore, it is reasonable that Cheese
Corn Flavor will be also ordered at the same time.
2. If a customer purchases Cheese Corn Flavor and Yolk Flavor at the same
time, there is 92.3% probability that the customer will order BBQ Flavor.
Both of Cheese Corn Flavor and Yolk Flavor belong to sweet flavors.
They are usually used in puffed snack, such as Taiwan Pei Tien energy 99
sticks and Japanese rice rolls. However, BBQ Flavor belongs to salty flavors.
In fact, transferring from sweet to salty is the current flavor development
direction of the Chinese flavor market. Hence, this rule perfectly represents
the trend of further flavor development.
The company can exploit the association rules listed above by applying those
in future marketing strategies. The sales can base on these rules to do products
recommendation and promotion. For instance, when a customer orders Cheese Corn
Flavor and Chives Flavor together, there is 90.9% that the customer is also interested
in Yolk Flavor. In order to increase sales, Yolk Flavor can be recommended to the
32
customer by providing samples before asking. What’s more, these rules can be also
used to guide the future internal technology development. The technical department
can pay more attention on improving the quality of those high prediction rate
products. For example, Sauced Beef Flavor, Cumin BBQ Flavor and BBQ Flavor are
the top three prediction rate products, they should be emphasized in the future internal
technical development schedule.
4.2.2 Result for the North China Region
Figure 4.7 Levels of Link between Two Products (North China)
The level of every two flavors connection is showed visualized on figure 4.7.
The following flavor sets have strong linked: Cumin BBQ Flavor and Sauced Beef
Flavor, Cumin BBQ Flavor and Yolk Flavor, Chives Flavor and Yolk Flavor, and
Cheese Corn Flavor and Yolk Flavor.
33
Table 4.5 Rule Statistics (North China)
Measurements Minimum Maximum Mean Stand.
Deviation
Condition Support 12.50% 59.38% 32.77% 8.70%
Confidence 90.00% 100.00% 95.93% 4.28%
Rule Support 12.50% 56.25% 31.26% 7.95 %
Lift 1.31 2.29 1.86 0.26
Deployability 0.00% 3.13 % 1.51 % 1.56 %
Number of Rules: 395
Table 4.6 Information for Most Frequent Items (North Region)
Item name Records (%) Conditions
(%)
Predictions
(%)
Kimchi flavor 68.75 9.77 11.76
Sauced beef flavor 62.50 9.49 8.22
Curry beef 59.38 11.19 4.82
Hot & Spice salt 59.38 10.76 1.42
Pepper beef steak 56.25 12.61 5.24
Tomato flavor 53.13 11.47 2.83
Crab flavor 53.13 13.03 2.97
Cheese corn flavor 53.13 11.47 11.47
Hot & Spice Sichuan 53.13 10.48 7.65
BBQ flavor 50.00 12.75 9.21
Chives flavor 50.00 13.03 7.65
Chicken flavor 43.75 14.87 7.51
Cumin BBQ 43.75 17.00 7.22
Pork steak 43.75 17.28 6.80
Yolk 40.63 16.43 5.24
34
Table 4.5 states the rule statistics. There are 395 rules were generated. The
range of support is 12.5% to 59.4%, range of confidence is 90% to 100%, and all
rules have a lift higher than 1.
Table 4.6 answers us the question between products and popularity. Kimchi
flavor is the most popular product in the original dataset, and its prediction percentage
is also the highest. That means Kimchi flavor has the highest probability to be
popular in future. This result is an important reference conditions for the following
valuable rules generation.
Table 4.7 Most Interesting Association Rule for North Region (2013 – 2015)
Antecedent Consequent
Rule 1 Hot & Spice Salt and BBQ Flavor Kimchi Flavor
Rule 2 Yolk and Pepper Beef Steak Flavor Cheese Corn Flavor
Rule 3 Hot & Spice Salt and Pork Steak Flavor BBQ Flavor
Rule 4 Hot & Spice Salt and Chives Flavor Sauced Beef Flavor
Rule 5 Pork Steak and Curry Beef Flavor Cheese Corn Flavor
Rule 6 Yolk and Pepper Beef Steak Kimchi Flavor
Rule 7 Cumin BBQ and Curry Beef Flavor Sauced Beef Flavor
Rule 8 Pork Steak and Curry Beef Flavor Sauced Beef Flavor
Rule 9 Pork Steak and Pepper Beef Steak Flavor BBQ Flavor
Rule 10 Hot & Spice Salt and Chicken Flavor Kimchi Flavor
Table 4.7 lists the top ten “interesting” association rules for the North China
region. Just like section 4.2.1, this result was also based on apriori rule sets
generation and analysis. (Full result is available in Appendix B, Table 4.) We sorted
all rules by both confidence and support. A rule with high confidence but low
support can provide us more unexpected information, which is defined as an
interesting rule. Then picking up the high probability rules especially for high
prediction products. The full results of rule sets generation and scoring are available
in Appendix B, Table 5. And the scores in tabular format are also available in
Appendix B, Table 6.
35
High affinity products:
1. If a customer purchases Hot & Spice Sichuan Flavor and Chicken Flavor
at the same time, there is high probability that the customer will order
Kimchi Flavor.
All of these three flavors belong to salty flavors. One of the main uses
of these flavors is jerky production. In fact, the jerky products have a wider
acceptance in this region. What’s more, the consumers in the North China
region prefer strong tastes than other regions. Kimchi Flavor may be the
further trend in jerky market. It can be combined with other flavors such as
Chicken Flavor to develop new product.
Therefore, for the manufactures that target jerky products in North
China region, it is reasonable for them to order these three flavors together.
This rule represents that, in North China region, some manufacturers may start
to develop new Kimchi Flavor end products.
All these rules can be considered in further marketing strategies making. It
provides sales man more interesting understanding for products recommendation. For
instance, when a customer orders Pork Steak Flavor and Curry Beef Flavor together,
the sales man can recommend Sauced Beef Flavor and Cheese Corn Flavor to the
customer. Although these two flavors are not commonly connected, the association
rules do find out the strong relationship between them. What’s more, the rules can
also help the company to improve their current recommendation combination. If a
customer suddenly change his or her usual purchases combination, company need to
realize the change and figure out what happened behind the change. Then, if the
customer changes the purchases because of any market strategies related reason,
company should have the new recommendation based on customers’ current
purchasing preferences.
36
4.2.3 Result for the South China Region
Figure 4.8 Levels of Link between Two Products (South China)
Figure 4.8 shows us the level of connections between two flavors. Cumin BBQ
Flavor, Yolk Flavor, Pork Steak Flavor, Chicken Flavor all have strong connections
to each other.
Table 4.8 Rule Statistics (South China)
Measurements Minimum Maximum Mean Stand.
Deviation
Condition Support 11.76 % 58.82% 30.29 % 8.70%
Confidence 90.00% 100.00% 96.59% 4.14%
Rule Support 11.76 % 52.94 % 29.07 % 7.97 %
Lift 1.53 3.09 1.95 0.36
Deployability 0.00% 5.88 % 1.21 % 1.47 %
Number of Rules: 383
Table 4.9 Information for Most Frequent Items (South China)
Item name Records (%) Conditions
(%)
Predictions
(%)
Sauced beef flavor 58.82 10.18 10.18
spices salt 58.82 8.36 4.18
Kimchi flavor 58.82 11.75 9.92
37
Cheese corn flavor 55.88 12.27 9.40
Curry beef 55.88 8.62 2.61
Tomato flavor 52.94 10.70 4.70
BBQ flavor 52.94 10.97 10.44
Pepper beef steak 52.94 9.66 4.44
Hot Sichuan flavor 52.94 9.40 8.09
Crab flavor 50.00 10.44 2.09
Chives flavor 50.00 12.27 10.18
Chicken flavor 41.18 19.58 8.36
Cumin BBQ 38.24 19.84 7.57
Yolk 38.24 19.32 5.48
Pork steak 32.35 20.10 2.35
Table 4.8 shows the basic statistics of the 383 rules. The range of support is
11.8 % to 58.8%, range of confidence is 90% to 100%, and all rules have a lift higher
than 1.
Based on table 4.9, we know that Sauced beef Flavor, Hot & Spice Salt
Flavor, and Kimchi Flavor are the products existing in 58% records. However, in the
prediction, the highest percentage of rules that has BBQ flavor.
Table 4.10 Most Interesting Association Rule for South China (2013 – 2015)
Antecedent Consequent
Rule 1 Pork Steak Flavor and Crab Flavor Chicken Flavor
Rule 2 Curry Beef Flavor and Chicken Flavor Cheese Corn Flavor
Rule 3 Yolk Flavor and Crab Flavor BBQ Flavor
Rule 4 Pepper Beef Steak and Chicken Flavor Kimchi Flavor
Rule 5 Cumin BBQ and Pepper Beef Steak BBQ Flavor
Rule 6 Yolk Flavor and Tomato Flavor Sauced Beef Flavor
Rule 7 Hot & Spice Salt and Chives Flavor Kimchi Flavor
Rule 8 Pork Steak Flavor and Crab Flavor Chives Flavor
Rule 9 Hot & Spice Salt and Chicken Flavor Cheese Corn Flavor
Rule 10 Crab Flavor and Cumin BBQ Flavor BBQ Flavor
38
Table 4.10 states the top ten “interesting” association rules for the North
China region. Just like section 4.2.1, this result was also based on apriori rule sets
generation and analysis. (Full result is available in Appendix B, Table 7.) Following
the high confidence and low support conditions, we can pick up the high probability
rules for high prediction products. The full results of rule sets generation and scoring
are available in Appendix B, Table 8. And the scores in tabular format are also
available in Appendix B, Table 9.
High affinity products:
1. If a customer purchases Pork Steak Flavor and Crab Flavor at the same
time, there is high probability that the customer will order Chives Flavor.
Pork Steak Flavor is one of the nationwide popular flavors. It can be
used in many different kinds of end products. So the purchasing of this flavor
is more stable than others. What’s more, Crab Flavor, as a fast growing
product, the acceptance of it is keep on increasing especially in South China.
Another product with a strong regional preference is Chives Flavor.
As a new product with growth potential, Chives Flavor becomes more popular
in the South China region. The popularity of this flavor is affected by the
dietary habits in South East Asia. It is one of the target markets for the cracker
manufacturers in South China region.
This rule represent a strong regional preference, which is valuable for
the company to make specific market strategies in this region.
2. If a customer purchases Yolk Flavor and Tomato Flavor at the same time,
there is high probability that the customer will order Sauced Beef Flavor.
Tomato Flavor is a long-history flavor in China. It is also a common
flavor exists in multiply kinds of snacks. Yolk Flavor, a sweet flavor, is one of
the high acceptance products in South China. It can be used in puffed food or
snacks. There is a market for both of these two products in South China
region.
Sauced Beef Flavor is a significant salty flavor, which was very
popular in North China. However, the acceptance of this flavor in South China
keeps on increasing.
39
This rule also represented the current flavor development trend in
China: customer preferences transfer from sweet to salty.
All these rules are useful for the company in marketing decision making.
More hidden information can be applied in products recommendation and promotion.
For instance, when Pork Steak Flavor and Crab Flavor exist in a transaction, there is
a very high probability that Chicken Flavor and Chives Flavor also exist. In another
word, when a customer orders Pork Steak Flavor and Crab Flavor together, he or she
may also want to order Chicken Flavor or Chives Flavor.
4.2.4 Result for the Mid China Region Figure 4.9 Levels of Link between Two Products (Mid China)
Figure 4.9 represent the different level of links between two flavors. In the
grapy, we can see that Chives Flavor, Yolk Flavor, and Pork Steak Flavor all have
strong links to each other. And Cumin BBQ Flavor also has strong links with Chives
Flavor, Chicken Flavor, Yolk Flavor and Pork Steak Flavor.
40
Table 4.11 Rule Statistics (Mid China)
Measurements Minimum Maximum Mean Stand.
Deviation
Condition Support 12.50 % 56.25% 31.36 % 8.39%
Confidence 90.00% 100.00% 96.95% 4.12%
Rule Support 12.50 % 53.13 % 30.24% 7.72 %
Lift 1.44 2.67 2 0.39
Deployability 0.00% 3.13 % 1.12 % 1.50%
Number of Rules: 424
Table 4.12 Information about Most Frequent Items (Mid China)
Item name Records (%) Conditions
(%)
Predictions
(%)
Sauced beef flavor 62.50 10.85 8.49
Cheese corn flavor 62.50 11.08 4.25
spices salt 59.38 7.31 4.72
Kimchi flavor 59.38 12.74 11.79
Hot sichuan 59.38 11.32 9.91
Curry beef 56.25 6.60 2.36
Pepper beef steak 53.13 8.02 4.01
Tomato flavor 50.00 9.20 1.89
BBQ flavor 46.88 15.09 11.79
Crab flavor 43.75 13.44 0.00
Chicken flavor 43.75 16.27 11.79
Cumin BBQ 40.63 18.87 10.38
Yolk 40.63 16.98 7.78
Pork steak 37.50 17.69 5.42
Chives flavor 37.50 17.69 5.42
41
Table 4.11 shows the basic statistics. There are 424 rules based on the aprior
analysis. The range of support is 12.5 % to 56.25%, range of confidence is 90% to
100%, and all rules have a lift higher than 1.
Table 4.12 states the information about most frequent flavors. Sauced Beef
Flavor has the highest appearance percentage in all 15 flavors. However, the highest
prediction flavors are Kimchi Flavor, BBQ Flavor, and Chicken Flavor.
Table 4.13 Most Interesting Association Rule for Mid Region (2013 – 2015)
Antecedent Consequent
Rule 1 Curry Beef and BBQ Flavor Chicken Flavor
Rule 2 Pepper Beef Steak and Cumin BBQ Flavor BBQ Flavor
Rule 3 Hot & Spice Salt and Cumin BBQ Kimchi Flavor
Rule 4 Pork Steak and Crab Flavor Cumin BBQ Flavor
Rule 5 Chives Flavor and Crab Flavor Kimchi Flavor
Rule 6 Crab Flavor and Yolk Flavor Hot & Spice Sichuan
Rule 7 Pork Steak Flavor and Crab Flavor BBQ Flavor
Rule 8 Curry Beef and Chicken Flavor BBQ Flavor
Rule 9 Hot & Spice Salt and BBQ Flavor Chicken Flavor
Rule 10 Crab Flavor and Yolk Flavor Cumin BBQ Flavor
Table 4.13 shows the most “interesting” association rules for the Mid China
region. Like section 4.2.1, apriori rule sets analysis was used to generate it. (Full table
is available in Appendix B, Table 10.) After sorting result from the highest
confidence and lowest support, we can pick up the rules by considering the
percentage of prediction. The full results of rule sets generation and scoring are
available in Appendix B, Table 11. And the scores in tabular format are also available
in Appendix B, Table 12.
High affinity products:
1. If a customer purchases Crab Flavor and Pork Steak Flavor at the same
time, there is high probability that the customer will order BBQ Flavor.
Both of the Pork Steak Flavor and BBQ Flavor are typical salty
flavors. And the Crab Flavor as a fast growing flavor becomes more and more
42
popular in multiple regions. All of these three flavors are often used in nuts
and beans products. What’s more, Mid China region distribute a plenty of
small nuts and beans snacks manufacturers. So this region has a wider nut
snacks market than other regions.
This rule can be used for targeting the nuts snacks manufacturers in
the Mid China region.
2. If a customer purchases Yolk Flavor and Crab Flavor at the same time,
there is high probability that the customer will order Hot & Spice Sichuan
Flavor.
Yolk Flavor and Crab Flavor are usually used in snacks production in
the past few years. Even in the Mid China region, especially Hu’nan and
Hu’bei province, which has a fondness for spicy flavors, these two flavors still
have a growing development.
In fact, Hot & Spice Sichuan Flavor is a flavor with a very strong
regional preference. It can only used in jerky or meat products in the past
because of the technology limitation. However, the developing production
technology in today provides more opportunities to this flavor. Several
manufacturers in Mid China already start to launch new nuts even puffed
products with Hot & Spice Sichuan Flavor to satisfy the end-customer in this
region.
For the manufacturers, which focus on snacks production in Mid
China region, they do have a high probability to purchase these three products
at the same time.
By considering the rules, the sales man can provide more targeted
recommendation to customers. For instance, if a customer orders Yolk Flavor and
Crab Flavor at the same time, sales man can recommend to him or her two flavors,
Hot & Spice Sichuan Flavor and Cumin BBQ Flavor based on the rules.
43
4.2.5 Result for the East China Region Figure 4.10 Levels of Link between Two Products (East China)
Figure 4.10 shows the level of links between every two flavors based on the
data in Mid China region. Chives Flavor, Chicken Flavor, and Cumin BBQ Flavor
are strongly linked to Pork Steak Flavor. And Cumin BBQ Flavor also links with
Chives Flavor, Chicken Flavor, Yolk Flavor, BBQ Flavor and Pork Steak Flavor.
Table 4.14 Rule Statistics (East China)
Measurements Minimum Maximum Mean Stand.
Deviation
Condition Support 11.76% 61.76% 29.36% 10.40%
Confidence 90.00% 100.00% 96.55% 4.05%
Rule Support 11.76% 55.88% 28.10% 9.55%
Lift 1.46 2.83 2.02 0.33
Deployability 0.00% 5.88% 1.26% 1.47%
Number of Rules: 376
44
Table 4.15 Information for Most Frequent Items (East China)
Item name Records (%) Conditions
(%)
Predictions
(%)
Pepper Beef Steak Flavor 61.76 7.71 5.32
Tomato Flavor 58.82 10.64 3.19
Sauced Beef Flavor 55.88 5.85 9.04
Curry Beef Flavor 55.88 9.31 3.72
Hot & Spice Salt Flavor 55.88 5.59 0.53
Kimchi Flavor 55.88 13.03 12.77
Hot & Spice Sichuan Flavor 55.88 9.84 7.45
Cheese Corn Flavor 52.94 10.64 9.04
Crab Flavor 47.06 12.77 1.60
BBQ Flavor 44.12 13.56 11.44
Chicken Flavor 41.18 19.15 9.04
Cumin BBQ Flavor 41.18 18.09 9.84
Yolk Flavor 41.18 13.03 4.79
Chives Flavor 41.18 19.95 8.78
Pork Steak Flavor 35.29 23.94 3.46
Table 4.14 states the basic statistics about the rules based on East China
region dataset. It generated 376 rules by aprior method. The range of support is
11.78 % to 61.76%, range of confidence is 90% to 100%, and all rules have a lift
higher than 1.
Table 4.15 lists all 15 flavors’ predictions and records information. Pepper
Beef Steak Flavor is the most frequent product in dataset. There are 61.78% records
has Pepper Beef Steak Flavor. However, the highest prediction flavors are Kimchi
Flavor, which has a 12.77% prediction.
Table 4.16 Most Interesting Association Rule for East Region (2013 – 2015)
Antecedent Consequent
Rule 1 Pork Steak Flavor and Crab Flavor Chicken Flavor
Rule 2 Pork Steak Flavor and Tomato Flavor Kimchi Flavor
45
Rule 3 Chicken Flavor and Tomato Flavor Cumin BBQ Flavor
Rule 4 Yolk Flavor and Tomato Flavor Sauced Beef Flavor
Rule 5 Hot & Spice Salt and BBQ Flavor Cheese Corn Flavor
Rule 6 Crab Flavor and Yolk Flavor Kimchi Flavor
Rule 7 Pork Steak Flavor and Pepper Beef Steak Sauced Beef Flavor
Rule 8 Chives Flavor and Curry Beef Flavor Kimchi Flavor
Rule 9 Curry Beef Flavor and BBQ Flavor Cheese Corn Flavor
Rule 10 Chives Flavor and Tomato Flavor BBQ Flavor
Table 4.16 lists top ten valuable rules in Mid China region. As same as the
sections before, we used the same method, aprior, to generate the result. (Full table is
available in Appendix B, Table 13.) Considering the correlation variables, we chose
the rules related to high prediction flavors with high confidence but low support. Full
rule sets generation and scoring information is also available in Appendix B, Table 14.
And the scores in tabular format are available in Appendix B, Table 15.
High affinity products:
1. If a customer purchases Pork Steak Flavor and Tomato Flavor at the same
time, there is a high probability that the customer will order Kimchi
Flavor.
The popularity trend of Kimchi Flavor is from north to south. In
several provinces close to the North China region such as Shandong, Anhui,
the unique sweet spice taste of Kimchi Flavor can satisfied the customer
demand in this region. And it can be perfectly combined with other typical
salty flavor such as Pork Steak Flavor and Tomato Flavor to develop new end
products. This rule may represent the new flavor innovation in the East China.
2. If a customer purchases Curry Beef Flavor and BBQ Flavor at the same
time, there is a high probability that the customer will order Cheese Corn
Flavor.
Both of Curry Beef Flavor and BBQ Flavor are traditional salty
flavors, which usually used in snacks and biscuit products. They are also the
main base flavor in many chips products. Cheese Corn Flavor, a flavor
46
affected by western taste, is popular among the youth. And it is also an
expressive flavor when combining with other base flavors. In fact, the East
China region, such as Shanghai, is very adaptable to new products. This rule
may also represent the new product innovation trend in snack market.
Using the rules listed above, sales man can provide customers more targeted
products in East China region. For instance, if a customer orders Pork Steak Flavor
and Crab Flavor together, there is a high probability that he or she will be also
interested in Chicken Flavor based on the rules.
4.2.6 Result for the South West China Region Figure 4.11 Levels of Link between Two Products (South West China)
Figure 4.11 shows the flavors’ relationship in South West China. The heavier
line means the stronger relationship between two flavors. Pork Steak Flavor and Yolk
Flavor are strongly linked to each other. What’s more, Yolk Flavor and Pork Steak
Flavor are linked to Chicken Flavor.
47
Table 4.17 Rule Statistics (South West China)
Measurements Minimu
m
Maximum Mean Stand.
Deviation
Condition Support (%) 12.12 54.55 30.67 9.25
Confidence (%) 90.00 100.00 97.19 3.92
Rule Support (%) 12.12 51.52 29.62 8.51
Lift 1.41 2.75 1.90 0.33
Deployability (%) 0.00 3.03 1.05 1.44
Number of Rules: 309
Table 4.18 Information for Most Frequent Items (South West China)
Item name Records (%) Conditions (%) Predictions
(%)
Sauced beef flavor 63.64 8.74 15.21
Pepper beef steak 60.61 6.80 5.83
Tomato flavor 57.58 8.09 1.62
Cheese corn flavor 57.58 8.41 5.18
Hot & Spices Salt 57.58 9.06 0.97
Curry beef 54.55 9.39 6.15
Chives flavor 54.55 12.30 13.92
Hot sichuan 54.55 10.68 8.74
Crab flavor 48.48 6.15 0.00
BBQ flavor 48.48 15.53 12.94
Cumin BBQ 48.48 14.24 11.33
Kimchi flavor 45.45 12.94 0.97
Chicken flavor 42.42 22.33 8.74
Pork steak 36.36 24.27 2.59
Yolk 36.36 24.60 5.83
Table 4.17 shows the rules’ basic statistics in the South West China region.
309 rules were generated by aprior method based on the regional dataset. The range
48
of support is 12.12 % to 54.55%, range of confidence is 90% to 100%, and all rules
have a lift higher than 1.
Table 4.18 shows all 15 flavors’ appearance rate and prediction rate based on
the provided data. Sauced Beef Flavor is the most popular flavor in original dataset. It
appeared in 63.64% records. The flavor with highest prediction percentage, 15.21%,
is also Sauced Beef Flavor.
Table 4.19 Most Interesting Association Rule for SouthWest China (2013 – 2015)
Antecedent Consequent
Rule 1 Yolk Flavor and Curry Beef Flavor Sauced Beef Flavor
Rule 2 Crab Flavor and Yolk Flavor BBQ Flavor
Rule 3 Pork Steak Flavor and Crab Flavor Chives Flavor
Rule 4 Hot & Spice Salt Flavor & Chicken Flavor BBQ Flavor
Rule 5 Chicken Flavor and Curry Beef Flavor BBQ Flavor
Rule 6 Yolk Flavor and Curry Beef Flavor Cumin BBQ Flavor
Rule 7 Crab Flavor and Chicken Flavor Cumin BBQ Flavor
Rule 8 Hot & Spice Salt Flavor and BBQ Flavor Sauced Beef Flavor
Rule 9 Yolk Flavor and Tomato Flavor Sauced Beef Flavor
Rule 10 Yolk Flavor and Tomato Flavor Chives Flavor
Table 4.19 shows the top ten interesting rules in South West China region. We
kept on using the aprior method to get the result. (Full table is available in Appendix
B, Table 16.)
In order to choose the most interesting rules, we ranking confidence at first,
then sorting the support from bottom. After that, we picked up the top ten interesting
rules by considering the prediction information. Full rule sets generation and scoring
information is available in Appendix B, Table 17. And the scores in tabular format
are available in Appendix B, Table 18.
49
High affinity products:
1. If a customer purchases Yolk Flavor and Curry Beef Flavor at the same
time, there is a high probability that the customer will order Cumin BBQ
Flavor.
The South West China region such as Yunnan province has varieties
quality beef products. Yolk Flavor is an essential flavor in beef products to
raise fresh. Curry Beef Flavor and Cumin BBQ Flavor are usually applied to
beef products. They together form the southwest featured taste. For the
manufacturers targeting beef products in this region, this rule is reasonable
and valuable in flavor recommendation.
The rules provide a better understanding on products relationships in South
West China region. For instance, if Yolk Flavor and Tomato Flavor are ordered
together, Sauced Beef Flavor and Chives Flavor are both good candidates in
recommendation based on the rules.
50
Chapter 5: Conclusions
5.1 General Discussion As a useful data mining technique, Market basket analysis can help up to find
out the uncovering connections between products. And it also used in analyzing the
customer purchasing behaviors. The results can provide more information for
decision-making about marketing strategy, inventory control, R & D development
and cross-sale strategies. The generated rules in this study can be used especially in
making decision on marketing strategy, cross-sale recommendations and future
internal research direction. And the company can also base on the regional results to
figure out the targeted strategies for different regions.
In this research, the number of transaction in regional datasets is as big as
expected. The results may be affected by unknown bias. And that also increase the
level of difficulty in mining valuable and interesting rules. However, the result cannot
provide perfectly prediction to every customers, the interesting rules are only the high
probability rules based on analysis. All generated rules are useful and actionable for
company.
5.2 Academic Contribution To date, market basket problem becomes more and more popular. Association
rule analysis has been sufficiently studied for the past few years. This study is
building on previous findings about mining association rules to provide valuable
information to the company. During the dataset adjustment, using the mean numbers
as the cut-off points to each product instead of a fixed number reduced the error.
Evaluating probability and prediction of all products provides more reasonable
meaning during the most valuable association rules choosing. Classifying the dataset
by region gives the company a better understanding of regional customers’ purchase
behaviors.
Major academic contributions:
• A true or false transaction-based dataset was adjusted from the original
dataset by using mean number for each product.
51
• Level of links between every two products in different regions was
visually represented.
• Association rules were generated with confidence, support, and lift.
• The most interesting rules in different regions were chose by
considering confidence, support, rule set probability, and product
prediction.
5.3 Business Contribution In recent years, more and more companies start to emphasize understanding
customer purchasing behaviors to increase sales. Market basket analysis is not
restricted to academic research. The number of application issues related to
association rules analysis is growing dramatically in multiple fields (Square).
Market basket analysis can help the company know more about their
customers’ purchases behaviors. It shows a lot of hidden connections between
different products. Therefore, decision-maker can implement marketing strategies
efficiently. In this study, all five regions have different rule generation results. In
another word, there is a product preference for different regions. Based on that,
company can make different marketing strategies in different regions to realize the
maximum profit.
5.4 Limitations of the study Even though market basket analysis is straightforward and efficient, it still has
some drawbacks and limitations.
• Raw dataset problems
Since market basket analysis is all based on data. If we are not able to
collect or choose the right and related data, the analysis results will not
provide enough valuable information to us.
• Mining association rules problems
Another major difficulty is the large number of the rules generated.
Most of them are trivial. It is hard to find valuable rules from
thousands rules. In this study, only using support and confidence are
not enough to find the most interesting rules.
52
5.5 Directions for Future Research This study only focused on 15 products sales information from 2013 to 2015.
The datasets for every region are small. There are a lot of hidden information between
products cannot be fully exposed. Future research could collect a larger dataset
includes more products and transactions. It can reduce the data bias and generate
more valuable results.
Additionally, there are more questions can be asked based on the association
rules. This study only considered the regional influence. The future study can pay
more attention on different influence variables, such as seasons, times, type of
customers, and type of products.
53
Bibliography Connor, Brendan. AI and Social Science. 23 Feb 2009. 17 8 2016.
Han, Jiawei and Micheline Kamber. Data Mining: Concepts and Techniques. San
Francisco: Morgan Kaufmann, 2001.
IBM. IBM SPSS Retail Market Basket Analysis. 2009.
Lanzi, Pier Luca. Data Mining: Association Rules. 6 December 2009.
Padoe, Iain. "Chapter 9: Market Basket Analysis and Association Rule." 2006. Iain
Pardoe. 15 8 2016.
<http://www.iainpardoe.com/teaching/dsc433/handouts/chapter9h.pdf>.
Ramageri, Bharati. "Data Mining Techniques and Applications." Indian Journal of
Computer Science and Engineering (n.d.).
Square, Loyalty. Market Basket Analysis. n.d. 20 8 2016.
<http://loyaltysquare.com/mba.php>.
Tan, Pang Ning, Michael Steinbach and Vipin Kumar. Introduction to Data Mining.
Boston: Pearson Addison Wesley, 2005.
54
Appendices
Appendix A: Data Description
Table 1: Abbreviation Descriptions List of Abbreviation
TF Tomato Flavor ��风�调�� CF Crab Flavor ��风�调��
SBF Sauced Beef Flavor 酱����调�� CCF Cheese Corn Flavor �����调�� BQF Barbecue Flavor 烧��调�� PBS Pepper Beef Steak Flavor �����调�� CKF Chicken Flavor 鸡��调�� CBF Curry Beef Flavor �喱���调�� CBQ Cumin Barbecue Flavor ���烧味调�� HSS Hot and Spicy Salt Flavor �盐�调�� PSF Pork Steak Flavor 红烧���调�� YF Yolk Flavor ���调�� KF Kimchi Flavor 韩����调��
CVF Chives Flavor ���调�� HSC Hot and Spicy Sichuan Flavor �����调��
Table 2: Adjusted Dataset
YEAR
REGION
MONTH
TF
CF
SBF
CCF
BQF
PBS
CKF
CBF
CBQ
HSS
PSF
YF
KF
CVF
HSC
2013
North China
Jan. 1 0 1 0 0 1 1 1 1 1 0 0 1 0 0 Feb. 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Mar. 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Apr. 1 1 0 0 0 0 0 0 0 0 1 0 0 0 0 May. 0 1 1 0 0 1 1 0 0 0 0 0 0 0 0 Jun. 0 1 1 1 1 0 0 1 1 1 1 1 1 1 1 Jul. 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Aug. 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 Sep. 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 Oct. 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Nov. 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 Dec. 0 0 0 1 1 0 1 1 1 1 1 1 1 1 1
2014
Jan. 0 0 1 0 1 1 1 1 0 0 0 0 0 0 1 Feb. 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Mar. 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Apr. 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 May. 0 0 1 1 0 0 0 0 1 0 0 0 0 0 0 Jun. 0 0 1 0 1 0 1 1 1 1 1 1 0 1 0 Jul. 1 1 1 1 1 1 1 1 1 1 1 0 1 0 1 Aug. 1 1 1 1 1 0 1 1 1 1 0 1 1 0 0 Sep. 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 Oct. 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1
55
Nov. 1 0 0 1 1 1 1 1 1 1 1 1 1 1 0 Dec. 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1
2015
Jan. 0 1 0 0 1 0 1 0 1 0 1 1 0 1 1 Feb. 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Mar. 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Apr. 1 1 1 0 0 1 0 0 1 0 0 0 0 0 0 May. 0 0 0 0 0 0 1 0 0 1 0 0 1 0 0 Jun. 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Jul. 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 Aug. 0 1 1 1 1 1 1 1 1 0 1 1 1 0 1 Sep. 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 Oct. 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Nov. 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Dec. 1 1 1 1 1 1 1 1 0 1 1 0 1 1 1
2013
South Ch
ina
Jan. 1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 Feb. 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Mar. 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Apr. 0 1 0 0 0 0 0 0 1 0 0 0 0 0 0 May. 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 Jun. 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 Jul. 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 Aug. 1 0 1 1 1 1 0 1 0 1 1 0 0 1 1 Sep. 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Oct. 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 Nov. 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Dec. 1 0 1 1 0 1 1 1 1 1 1 1 1 1 1
2014
Jan. 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 Feb. 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Mar. 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 Apr. 0 1 0 0 0 0 0 0 0 1 0 1 0 1 0 May. 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 Jun. 0 0 1 1 1 1 1 1 1 0 1 1 1 1 1 Jul. 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Aug. 0 1 1 1 1 1 1 1 0 1 1 1 1 0 1 Sep. 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1 Oct. 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Nov. 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Dec. 1 0 1 1 1 0 1 1 1 1 0 1 1 1 1
2015
Jan. 0 1 1 1 1 0 1 0 1 0 1 1 0 1 0 Feb. 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Mar. 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Apr. 0 1 1 0 0 0 0 0 0 1 0 0 0 0 0 May. 0 1 0 0 1 1 0 0 0 0 0 0 0 0 0 Jun. 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 Jul. 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Aug. 1 1 1 1 1 1 1 1 1 1 0 1 1 1 0 Sep. 1 0 1 1 1 1 1 1 1 1 1 1 1 0 1 Oct. 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 Nov. 0 1 0 1 1 1 1 1 1 1 1 1 1 1 1 Dec. 1 0 0 0 1 1 1 1 1 1 1 1 1 1 1
2013
Mid China
Jan. 0 0 1 0 1 1 1 1 1 1 1 1 1 1 1 Feb. 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Mar. 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Apr. 0 1 1 0 1 0 0 0 0 0 0 0 0 0 0 May. 1 0 0 0 0 1 0 0 0 0 0 1 0 0 0 Jun. 0 0 1 0 1 0 1 1 1 1 1 1 1 1 1 Jul. 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Aug. 1 1 1 1 1 1 1 1 1 1 1 0 1 1 0 Sep. 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Oct. 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 Nov. 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Dec. 0 1 0 0 0 0 0 1 0 1 1 0 1 1 1
2 0 1 4 Jan. 0 0 1 0 1 1 1 1 1 1 1 1 1 1 1
56
Feb. 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Mar. 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Apr. 1 1 1 0 0 0 0 0 0 0 0 0 1 0 0 May. 0 1 0 0 0 0 0 0 0 0 0 0 0 1 0 Jun. 0 1 1 1 1 1 1 1 1 0 1 1 1 1 1 Jul. 1 0 1 1 0 1 1 1 1 1 1 1 1 0 1 Aug. 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 Sep. 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 Oct. 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 Nov. 0 0 1 0 1 1 1 1 1 1 1 1 1 1 1 Dec. 1 1 1 1 0 1 1 1 1 1 1 0 1 1 1
2015
Jan. 0 0 1 0 1 1 1 1 1 1 1 1 1 1 1 Feb. 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Mar. 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Apr. 0 1 0 0 0 0 0 0 0 0 0 0 1 0 0 May. 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 Jun. 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 Jul. 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Aug. 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 Sep. 0 0 1 1 1 1 1 1 1 1 1 1 1 0 1 Oct. 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Nov. 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 Dec. 0 1 1 1 1 1 1 0 1 1 1 1 1 1 1
2013
East China
Jan. 1 1 0 1 0 0 1 1 0 0 0 0 0 0 0 Feb. 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Mar. 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Apr. 0 0 1 0 0 0 0 0 0 0 0 1 0 0 0 May. 1 1 1 1 0 1 0 1 0 0 0 0 0 0 0 Jun. 1 0 0 1 1 1 1 1 1 0 1 0 1 1 1 Jul. 0 0 1 1 1 1 1 0 1 1 1 1 0 1 1 Aug. 1 0 1 1 1 1 0 1 1 1 1 1 1 1 1 Sep. 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Oct. 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 Nov. 0 0 1 0 1 1 1 1 1 1 1 1 1 1 1 Dec. 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1
2014
Jan. 1 1 0 1 0 0 1 1 0 0 0 0 0 0 0 Feb. 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Mar. 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 Apr. 1 1 0 0 1 0 0 0 0 0 0 0 0 1 0 May. 1 1 1 0 0 0 1 0 0 1 0 0 0 0 0 Jun. 0 0 1 1 1 1 1 1 1 0 1 1 1 1 1 Jul. 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Aug. 1 0 0 1 1 1 0 1 1 1 0 1 1 1 0 Sep. 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Oct. 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 Nov. 0 0 1 1 1 1 1 1 1 1 1 1 1 1 0 Dec. 1 0 1 1 1 1 0 1 1 1 1 1 1 1 1
2015
Jan. 1 0 0 1 0 0 0 1 0 0 0 0 0 0 0 Feb. 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Mar. 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Apr. 0 0 0 0 0 0 1 0 1 0 0 0 0 1 0 May. 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 Jun. 0 1 1 1 1 1 1 1 1 1 1 1 1 0 1 Jul. 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 Aug. 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 Sep. 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Oct. 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Nov. 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Dec. 1 1 1 0 1 0 1 1 1 1 1 1 1 1 1
2013
South
West
Jan. 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 Feb. 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Mar. 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 Apr. 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0
57
May. 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Jun. 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 Jul. 0 1 1 1 1 1 1 1 1 1 1 1 0 1 1 Aug. 1 0 1 1 1 1 1 1 1 1 0 1 0 1 1 Sep. 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Oct. 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Nov. 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 Dec. 1 1 0 1 0 1 1 1 1 1 1 1 0 1 1
2014
Jan. 1 0 0 0 0 0 0 0 0 1 0 0 0 0 1 Feb. 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Mar. 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 Apr. 0 1 0 0 0 0 0 0 1 0 1 0 0 0 0 May. 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 Jun. 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 Jul. 0 0 1 1 1 1 1 1 1 1 1 1 0 0 1 Aug. 1 1 1 1 0 1 1 1 1 0 1 0 1 1 1 Sep. 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Oct. 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 Nov. 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Dec. 1 1 0 1 1 1 1 0 1 1 1 1 1 1 1
2015
Jan. 1 0 0 0 0 0 0 0 0 0 1 1 0 0 1 Feb. 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Mar. 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 Apr. 0 0 0 1 0 1 0 0 0 0 0 0 0 0 0 May. 0 1 0 0 1 1 0 0 1 0 0 0 0 1 0 Jun. 1 0 1 0 1 0 1 1 0 1 1 0 1 1 1 Jul. 1 1 1 1 1 0 1 1 1 1 1 1 1 1 1 Aug. 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 Sep. 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 Oct. 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 Nov. 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 Dec. 1 1 0 1 0 1 1 1 1 1 1 1 1 1 1
58
Appendix B: Results
Table 1 Result for All Regions Consequent Antecedent Support % Confidence % Lift
1 CCF CF and TF 25.556 100 2.571
2 CKF CCF and CVF 12.222 100 2.093
3 CBF CCF and PBS 13.333 100 1.915
4 CKF TF and CBF 10 100 2.093
5 PSF CVF and HSC 18.889 100 2.812
6 SBF CVF and PBS 18.889 100 1.957
7 PSF HSC and Yolk 23.889 100 2.812
8 CBF PSF and HSS 15 100 2.25
9 CBF PSF and KF 26.111 100 2.25
10 CBF PSF and PBS 20.556 100 2.25
11 CBF PSF and CBF 22.778 100 2.25
12 CBF PSF and SBF 26.111 100 2.25
13 SBF PSF and PBS 20.556 100 1.957
14 SBF PBS and BQF 30 100 1.957
15 PBS HSS and CBF 37.222 98.507 1.927
16 CBF KF and BQF 31.667 98.246 2.211
17 SBF BQF and CBF 31.667 98.246 1.922
18 CCF CF 28.889 98.077 2.522
19 CBF CVF and SBF 23.889 97.674 2.198
20 CBF CVF and KF 22.778 97.561 2.195
21 SBF PSF and CBF 22.778 97.561 1.909
22 CBF Yolk and KF 22.778 97.561 2.195
23 CBF CVF and CBF 21.111 97.368 2.191
24 SBF CVF and CBF 21.111 97.368 1.905
25 BQF PSF and PBS 20.556 97.297 2.06
26 CBF CVF and HSC 18.889 97.059 2.184
27 CKF CVF and HSC 18.889 97.059 2.031
28 BQF CVF and HSC 18.889 97.059 2.055
29 CBF CVF and PBS 18.889 97.059 2.184
30 CBF HSS and SBF 35 96.825 1.854
31 BQF PSF and HSS 15 96.296 2.039
32 CBF PSF and HSS 15 96.296 1.844
33 SBF PSF and HSS 15 96.296 1.884
34 CBF PSF and BQF 29.444 96.226 2.165
35 PBS HSS and KF 29.444 96.226 1.883
36 CBF TF and PBS 14.444 96.154 1.841
59
37 CBF PBS and SBF 42.222 96.053 1.839
38 PBS HSS and CBF 27.778 96 1.878
39 CBF HSS and CBF 27.778 96 1.838
40 CCF CF and BQF 13.333 95.833 2.464
41 CBF CVF and HSS 13.333 95.833 2.156
42 CBF CVF and HSS 13.333 95.833 1.835
43 SBF CVF and HSS 13.333 95.833 1.875
44 CBF HSC and KF 26.667 95.833 2.156
45 BQF PSF and SBF 26.111 95.745 2.028
46 SBF HSS and BQF 26.111 95.745 1.873
47 SBF Yolk and CBF 25.556 95.652 1.871
48 CBF CVF and PSF 25 95.556 2.15
49 CCF CF and SBF 12.222 95.455 2.455
50 SBF HSC and CBF 24.444 95.455 1.868
51 PBS HSS and CKF 24.444 95.455 1.868
52 CBF HSS and CKF 24.444 95.455 1.828
53 SBF CBF and CBF 35.556 95.312 1.865
54 CBF CCF and KF 11.667 95.238 1.824
55 SBF Yolk and PBS 23.333 95.238 1.863
56 PBS HSS and SBF 35 95.238 1.863
57 CKF CVF and KF 22.778 95.122 1.991
58 BQF PSF and CBF 22.778 95.122 2.014
59 SBF CBF and PBS 33.889 95.082 1.86
60 CCF CF and CKF 11.111 95 2.443
61 CCF CF and CBF 10.556 94.737 2.436
62 SBF CF and CBF 10.556 94.737 1.854
63 CBF PBS and BQF 30 94.444 1.809
64 CBF HSS and KF 29.444 94.34 1.807
65 Yolk CVF and HSC 18.889 94.118 2.259
66 BQF CVF and PBS 18.889 94.118 1.993
67 CBF HSC and BQF 27.778 94 2.115
68 BQF CVF and Yolk 27.222 93.878 1.988
69 BQF CVF and CKF 27.222 93.878 1.988
70 SBF KF and CBF 36.111 93.846 1.836
71 CBF KF and PBS 35 93.651 1.793
72 BQF CVF and CBF 26.111 93.617 1.982
73 BQF PSF and KF 26.111 93.617 1.982
74 CBF CBF and PBS 33.889 93.443 1.789
75 Yolk CVF and PSF 25 93.333 2.24
76 CKF CVF and PSF 25 93.333 1.953
77 BQF CVF and PSF 25 93.333 1.976
60
78 PBS HSC and CBF 24.444 93.182 1.823
79 KF HSS and CKF 24.444 93.182 2.15
80 SBF CKF and CBF 32.222 93.103 1.822
81 BQF CVF and SBF 23.889 93.023 1.97
82 SBF KF and BQF 31.667 92.982 1.819
83 CBF BQF and CBF 31.667 92.982 2.092
84 CBF Yolk and PBS 23.333 92.857 1.778
85 CBF PBS and CKF 30.556 92.727 1.776
86 SBF PBS and CKF 30.556 92.727 1.814
87 BQF CVF and KF 22.778 92.683 1.963
88 PSF Yolk and KF 22.778 92.683 2.607
89 BQF Yolk and KF 22.778 92.683 1.963
90 BQF CVF 30 92.593 1.961
91 PBS PSF and HSS 15 92.593 1.812
92 CBF PBS and BQF 30 92.593 2.083
93 CBF KF and SBF 36.667 92.424 1.77
94 BQF CCF and Yolk 14.444 92.308 1.955
95 Yolk CVF and CBF 21.111 92.105 2.211
96 BQF CVF and CBF 21.111 92.105 1.95
97 SBF KF and PBS 35 92.063 1.801
98 Yolk CVF and BQF 27.778 92 2.208
99 CKF CVF and BQF 27.778 92 1.926
100 SBF HSS and CBF 27.778 92 1.8
101 CBF PSF and PBS 20.556 91.892 1.76
102 CBF HSC and SBF 27.222 91.837 2.066
103 BQF HSC and SBF 27.222 91.837 1.945
104 PBS CVF and HSS 13.333 91.667 1.793
105 BQF CVF and HSS 13.333 91.667 1.941
106 CBF HSS and PBS 40 91.667 1.755
107 PSF CVF and CBF 26.111 91.489 2.573
108 Yolk CVF and CBF 26.111 91.489 2.196
109 CKF CVF and CBF 26.111 91.489 1.915
110 CBF HSS and BQF 26.111 91.489 1.752
111 KF CKF and CBF 32.222 91.379 2.109
112 CKF KF and BQF 31.667 91.228 1.909
113 CBF CVF and PBS 18.889 91.176 1.746
114 BQF PSF and CBF 31.111 91.071 1.929
115 SBF HSS and CBF 37.222 91.045 1.781
116 Yolk CCF and CVF 12.222 90.909 2.182
117 BQF CCF and CVF 12.222 90.909 1.925
118 SBF HSS and CKF 24.444 90.909 1.779
61
119 KF PBS and CKF 30.556 90.909 2.098
120 PBS KF and CBF 36.111 90.769 1.776
121 SBF CBF and BQF 36.111 90.769 1.776
122 Yolk CVF 30 90.741 2.178
123 CKF CVF 30 90.741 1.899
124 CBF PSF and CKF 30 90.741 2.042
125 CKF CVF and SBF 23.889 90.698 1.898
126 CBF KF and CKF 35.556 90.625 2.039
127 CKF CCF and KF 11.667 90.476 1.894
128 SBF CCF and KF 11.667 90.476 1.77
129 CKF TF and KF 11.667 90.476 1.894
130 CBF TF and KF 11.667 90.476 1.733
131 CKF HSC and CBF 28.889 90.385 1.892
132 CBF HSC and CKF 28.889 90.385 2.034
133 BQF HSC and CBF 28.889 90.385 1.914
134 KF CKF and SBF 34.444 90.323 2.084
135 PSF CVF and KF 22.778 90.244 2.538
136 SBF CVF and KF 22.778 90.244 1.766
137 KF PSF and CBF 22.778 90.244 2.083
138 CBF PBS 51.111 90.217 1.728
139 TF CF and CCF 28.333 90.196 2.165
140 PSF Yolk and CBF 28.333 90.196 2.537
141 BQF Yolk and CBF 28.333 90.196 1.91
142 SBF HSC and BQF 27.778 90 1.761
143 CKF CVF and Yolk 27.222 89.796 1.879
144 Yolk CVF and CKF 27.222 89.796 2.155
145 CBF Yolk and SBF 27.222 89.796 1.719
146 CBF CBF and SBF 37.778 89.706 1.718
147 CKF HSC and KF 26.667 89.583 1.875
148 KF CVF and CBF 21.111 89.474 2.065
149 CKF CVF and CBF 21.111 89.474 1.873
150 PBS BQF and CBF 31.667 89.474 1.751
151 CBF KF and SBF 36.667 89.394 2.011
152 CBF BQF and SBF 36.667 89.394 2.011
153 SBF CVF and CBF 26.111 89.362 1.748
154 CKF PSF and KF 26.111 89.362 1.87
155 SBF HSC and PBS 26.111 89.362 1.748
156 PBS HSS and BQF 26.111 89.362 1.748
157 KF CBF and CKF 36.111 89.231 2.059
158 KF PSF and PBS 20.556 89.189 2.058
159 CBF SBF 51.111 89.13 1.707
62
160 KF CBF and CBF 35.556 89.062 2.055
161 PBS CBF and CBF 35.556 89.062 1.743
162 PBS CBF and SBF 45.556 89.024 1.742
163 KF PSF and HSS 15 88.889 2.051
164 CBF CKF and SBF 34.444 88.71 1.996
165 SBF HSS and KF 29.444 88.679 1.735
166 KF CBF and PBS 33.889 88.525 2.043
167 TF CF 28.889 88.462 2.123
168 CF CCF and TF 28.889 88.462 3.062
169 CKF CCF and Yolk 14.444 88.462 1.852
170 KF HSC and CBF 28.889 88.462 2.041
171 PSF CVF and SBF 23.889 88.372 2.485
172 Yolk CVF and SBF 23.889 88.372 2.121
173 CKF HSC and Yolk 23.889 88.372 1.85
174 PBS CBF 52.222 88.298 1.728
175 KF CVF and HSC 18.889 88.235 2.036
176 SBF CVF and HSC 18.889 88.235 1.726
177 Yolk CVF and PBS 18.889 88.235 2.118
178 KF CVF and PBS 18.889 88.235 2.036
179 CKF CVF and PBS 18.889 88.235 1.847
180 PBS Yolk and HSS 18.889 88.235 1.726
181 CBF Yolk and HSS 18.889 88.235 1.69
182 CBF CVF and BQF 27.778 88 1.98
183 KF HSS and CBF 27.778 88 2.031
184 SBF PBS and CBF 46.111 87.952 1.721
185 PBS CKF and CBF 32.222 87.931 1.72
186 PBS KF and SBF 36.667 87.879 1.719
187 Yolk CVF and KF 22.778 87.805 2.107
188 CVF Yolk and KF 22.778 87.805 2.927
189 SBF Yolk and KF 22.778 87.805 1.718
190 CBF CVF and Yolk 27.222 87.755 1.974
191 CBF CVF and CKF 27.222 87.755 1.974
192 CBF Yolk and SBF 27.222 87.755 1.974
193 CBF KF and CBF 36.111 87.692 1.973
194 CBF PSF 35.556 87.5 1.969
195 TF CF and BQF 13.333 87.5 2.1
196 Yolk CVF and HSS 13.333 87.5 2.1
197 KF CVF and HSS 13.333 87.5 2.019
198 CKF PSF and CBF 31.111 87.5 1.831
199 BQF HSC and KF 26.667 87.5 1.853
200 SBF HSC and KF 26.667 87.5 1.712
63
201 SBF KF and CKF 35.556 87.5 1.712
202 SBF CBF 52.222 87.234 1.707
203 SBF PSF and KF 26.111 87.234 1.707
204 KF PSF and SBF 26.111 87.234 2.013
205 CBF HSC and PBS 26.111 87.234 1.67
206 CBF KF 43.333 87.179 1.962
207 CBF CCF and SBF 17.222 87.097 1.668
208 CBF CKF and SBF 34.444 87.097 1.668
209 CBF CVF 30 87.037 1.958
210 CBF Yolk and CBF 25.556 86.957 1.957
211 PSF CVF and CBF 21.111 86.842 2.442
212 CBF PSF and Yolk 29.444 86.792 1.953
213 CKF PSF and Yolk 29.444 86.792 1.817
214 CKF PSF and BQF 29.444 86.792 1.817
215 SBF KF and CBF 37.778 86.765 1.698
216 KF CBF and SBF 37.778 86.765 2.002
217 BQF CBF and SBF 37.778 86.765 1.837
218 CBF PSF and HSC 28.889 86.538 1.947
219 PSF HSC and CBF 28.889 86.538 2.434
220 SBF HSC and CBF 28.889 86.538 1.693
221 KF HSC and CBF 24.444 86.364 1.993
222 CBF HSC and CBF 24.444 86.364 1.943
223 BQF HSC and CBF 24.444 86.364 1.829
224 PBS TF and CBF 16.111 86.207 1.687
225 KF CBF and BQF 36.111 86.154 1.988
226 BQF CBF and CKF 36.111 86.154 1.824
227 CKF CBF and BQF 36.111 86.154 1.803
228 CBF CKF and BQF 36.111 86.154 1.938
229 KF CVF and SBF 23.889 86.047 1.986
230 CBF CVF and SBF 23.889 86.047 1.648
231 CBF HSC and Yolk 23.889 86.047 1.936
232 PSF HSC and BQF 27.778 86 2.419
233 CBF KF and BQF 31.667 85.965 1.646
234 KF BQF and CBF 31.667 85.965 1.984
235 PBS TF and KF 11.667 85.714 1.677
236 SBF TF and KF 11.667 85.714 1.677
237 PSF CVF and Yolk 27.222 85.714 2.411
238 PSF CVF and CKF 27.222 85.714 2.411
239 KF HSC and SBF 27.222 85.714 1.978
240 PBS HSC and SBF 27.222 85.714 1.677
241 CBF HSC and SBF 27.222 85.714 1.641
64
242 BQF Yolk and SBF 27.222 85.714 1.815
243 CBF KF and PBS 35 85.714 1.929
244 BQF Yolk and CKF 30.556 85.455 1.81
245 Yolk PSF and CBF 22.778 85.366 2.049
246 PBS HSC and HSS 22.778 85.366 1.67
247 CKF Yolk and KF 22.778 85.366 1.787
248 CBF Yolk and KF 22.778 85.366 1.635
249 PSF CVF and PBS 18.889 85.294 2.399
250 SBF Yolk and HSS 18.889 85.294 1.669
251 CKF KF and CBF 37.778 85.294 1.785
252 PBS CBF and SBF 37.778 85.294 1.669
253 CBF TF and SBF 15 85.185 1.631
254 Yolk PSF and CKF 30 85.185 2.044
255 BQF PSF and CKF 30 85.185 1.804
256 KF CVF and CBF 26.111 85.106 1.964
257 CKF PSF and SBF 26.111 85.106 1.781
258 CBF PSF and SBF 26.111 85.106 1.63
259 CBF HSS and BQF 26.111 85.106 1.915
260 KF CBF 44.444 85 1.962
261 SBF CBF 44.444 85 1.663
262 BQF CF and CKF 11.111 85 1.8
263 SBF PSF and BQF 29.444 84.906 1.661
264 CKF KF and SBF 36.667 84.848 1.776
265 CBF BQF and SBF 36.667 84.848 1.625
266 PBS Yolk and CBF 25.556 84.783 1.659
267 SBF KF 43.333 84.615 1.656
268 CKF PSF and HSC 28.889 84.615 1.771
269 PSF HSC and CKF 28.889 84.615 2.38
270 SBF CBF and CKF 36.111 84.615 1.656
271 CBF CKF and CBF 32.222 84.483 1.901
272 SBF CVF and PSF 25 84.444 1.652
273 CKF PSF 35.556 84.375 1.766
274 CVF Yolk and CBF 28.333 84.314 2.81
275 SBF Yolk and CBF 28.333 84.314 1.65
276 CKF TF and Yolk 13.889 84 1.758
277 PSF CVF and BQF 27.778 84 2.362
278 KF HSC and BQF 27.778 84 1.938
279 CKF HSC and BQF 27.778 84 1.758
280 KF PSF and CBF 31.111 83.929 1.937
281 SBF PSF and CBF 31.111 83.929 1.642
282 BQF CKF and SBF 34.444 83.871 1.776
65
283 CBF KF and CBF 37.778 83.824 1.605
284 HSC PSF and PBS 20.556 83.784 2.038
285 BQF HSC and Yolk 23.889 83.721 1.773
286 PSF Yolk and CKF 30.556 83.636 2.352
287 CBF PBS and CKF 30.556 83.636 1.882
288 PSF CVF 30 83.333 2.344
289 CBF KF 43.333 83.333 1.596
290 KF TF and CBF 10 83.333 1.923
291 BQF TF and CBF 10 83.333 1.765
292 CKF CVF and HSS 13.333 83.333 1.744
293 CBF Yolk and PBS 23.333 83.333 1.875
294 SBF HSS and PBS 40 83.333 1.63
295 KF PBS and BQF 30 83.333 1.923
296 BQF PSF and Yolk 29.444 83.019 1.758
297 Yolk PSF and BQF 29.444 83.019 1.992
298 KF PSF and BQF 29.444 83.019 1.916
299 CBF HSS and KF 29.444 83.019 1.868
300 HSC PSF and KF 26.111 82.979 2.018
301 CBF CVF and KF 22.778 82.927 1.588
302 PBS PSF and CBF 22.778 82.927 1.622
303 CKF PSF and CBF 22.778 82.927 1.736
304 Yolk PSF 35.556 82.812 1.988
305 BQF PSF 35.556 82.812 1.754
306 CBF KF and CKF 35.556 82.812 1.586
307 BQF CBF and CBF 35.556 82.812 1.754
308 PBS HSS 48.333 82.759 1.619
309 Yolk PSF and HSC 28.889 82.692 1.985
310 BQF PSF and HSC 28.889 82.692 1.751
311 KF HSC and CKF 28.889 82.692 1.908
312 SBF PBS 51.111 82.609 1.616
313 PBS SBF 51.111 82.609 1.616
314 BQF Yolk and CBF 25.556 82.609 1.749
315 CKF Yolk and BQF 31.667 82.456 1.726
316 CKF Yolk and CBF 28.333 82.353 1.724
317 BQF KF and CBF 37.778 82.353 1.744
318 PBS CKF and SBF 34.444 82.258 1.609
319 KF CVF and PSF 25 82.222 1.897
320 Yolk PSF and CBF 31.111 82.143 1.971
321 CKF KF 43.333 82.051 1.717
322 BQF CBF and PBS 33.889 81.967 1.736
323 CBF CF and SBF 12.222 81.818 1.567
66
324 CBF HSS and CKF 24.444 81.818 1.841
325 PBS BQF and SBF 36.667 81.818 1.601
326 CKF HSC and SBF 27.222 81.633 1.709
327 PBS Yolk and SBF 27.222 81.633 1.597
328 PBS CVF and CBF 21.111 81.579 1.596
329 CKF KF and CBF 36.111 81.538 1.707
330 CBF CBF and BQF 36.111 81.538 1.561
331 HSC PSF and CKF 30 81.481 1.982
332 HSC PSF 35.556 81.25 1.976
333 CKF CBF 44.444 81.25 1.701
334 BQF CBF 44.444 81.25 1.721
335 PSF HSC and KF 26.667 81.25 2.285
336 BQF KF and CKF 35.556 81.25 1.721
337 HSC PSF and Yolk 29.444 81.132 1.973
338 HSC PSF and BQF 29.444 81.132 1.973
339 Yolk PSF and PBS 20.556 81.081 1.946
340 CKF PSF and PBS 20.556 81.081 1.697
341 HSS TF and KF 11.667 80.952 1.675
342 BQF Yolk and PBS 23.333 80.952 1.714
343 HSS KF and PBS 35 80.952 1.675
344 CKF CBF and SBF 37.778 80.882 1.693
345 CVF PSF and SBF 26.111 80.851 2.695
346 HSC PSF and SBF 26.111 80.851 1.967
347 Yolk PSF and KF 26.111 80.851 1.94
348 Yolk PSF and SBF 26.111 80.851 1.94
349 KF HSC and PBS 26.111 80.851 1.866
350 CBF HSC and PBS 26.111 80.851 1.819
351 BQF HSC and PBS 26.111 80.851 1.712
352 PBS KF 43.333 80.769 1.58
353 HSS TF and PBS 14.444 80.769 1.671
354 BQF HSC and CKF 28.889 80.769 1.71
355 CVF Yolk and BQF 31.667 80.702 2.69
356 CBF Yolk and BQF 31.667 80.702 1.816
357 CVF PSF and CBF 22.778 80.488 2.683
358 CBF HSC and HSS 22.778 80.488 1.541
359 HSC PSF and CBF 31.111 80.357 1.955
360 BQF KF and SBF 36.667 80.303 1.701
361 KF BQF and SBF 36.667 80.303 1.853
362 CBF CBF 44.444 80 1.532
363 TF CF and CKF 11.111 80 1.92
364 CVF Yolk and CKF 30.556 80 2.667
67
365 SBF CVF and BQF 27.778 80 1.565
366 BQF HSS and CBF 27.778 80 1.694
367 KF CKF and BQF 36.111 80 1.846
368 SBF CKF and BQF 36.111 80 1.565
369 SBF CVF 30 79.63 1.558
370 KF CVF and CKF 27.222 79.592 1.837
371 SBF CVF and CKF 27.222 79.592 1.557
372 HSS PBS and CBF 46.111 79.518 1.645
373 SBF CCF and CBF 18.889 79.412 1.554
374 PBS KF and CBF 37.778 79.412 1.554
375 CKF KF and PBS 35 79.365 1.661
376 SBF TF and CBF 16.111 79.31 1.552
377 CVF PSF and Yolk 29.444 79.245 2.642
378 CVF PSF and BQF 29.444 79.245 2.642
379 SBF CCF and PBS 13.333 79.167 1.549
380 PSF CVF and HSS 13.333 79.167 2.227
381 PBS HSC and KF 26.667 79.167 1.549
382 CBF HSC and KF 26.667 79.167 1.516
383 PBS CVF and SBF 23.889 79.07 1.547
384 HSS PBS and SBF 42.222 78.947 1.633
385 PBS KF and BQF 31.667 78.947 1.545
386 CKF BQF and CBF 31.667 78.947 1.652
387 CKF BQF and SBF 36.667 78.788 1.649
388 CVF PSF and KF 26.111 78.723 2.624
389 CBF CVF and CBF 26.111 78.723 1.507
390 CBF PSF and KF 26.111 78.723 1.507
391 PBS PSF and SBF 26.111 78.723 1.54
392 HSS CBF and PBS 33.889 78.689 1.628
393 PSF CBF and BQF 36.111 78.462 2.207
394 KF Yolk and CBF 28.333 78.431 1.81
395 CBF Yolk and CBF 28.333 78.431 1.502
396 CVF PSF and PBS 20.556 78.378 2.613
397 HSS PBS 51.111 78.261 1.619
398 PBS KF and CKF 35.556 78.125 1.529
399 HSC Yolk and KF 22.778 78.049 1.898
400 SBF TF and CBF 10 77.778 1.522
401 CVF PSF and CKF 30 77.778 2.593
402 HSC PSF and HSS 15 77.778 1.892
403 Yolk PSF and HSS 15 77.778 1.867
404 KF PSF and CKF 30 77.778 1.795
405 HSS PBS and BQF 30 77.778 1.609
68
406 CKF PBS and BQF 30 77.778 1.628
407 SBF BQF 47.222 77.647 1.519
408 BQF CKF and CBF 32.222 77.586 1.643
409 SBF CVF and Yolk 27.222 77.551 1.517
410 CVF Yolk and SBF 27.222 77.551 2.585
411 PSF HSC and SBF 27.222 77.551 2.181
412 PSF Yolk and SBF 27.222 77.551 2.181
413 BQF CCF and CKF 17.222 77.419 1.639
414 CKF HSS and KF 29.444 77.358 1.619
415 TF CF and SBF 12.222 77.273 1.855
416 CKF HSC and CBF 24.444 77.273 1.617
417 PSF Yolk and BQF 31.667 77.193 2.171
418 PSF KF and BQF 31.667 77.193 2.171
419 CBF HSS 48.333 77.011 1.475
420 CVF CCF and Yolk 14.444 76.923 2.564
421 SBF HSC and CKF 28.889 76.923 1.505
422 HSS KF and CBF 36.111 76.923 1.592
423 PBS CBF and BQF 36.111 76.923 1.505
424 CVF PSF and CBF 31.111 76.786 2.56
425 KF HSS and BQF 26.111 76.596 1.768
426 CKF CBF and CBF 35.556 76.562 1.602
427 CBF BQF 47.222 76.471 1.721
428 CKF BQF 47.222 76.471 1.601
429 CBF Yolk and HSS 18.889 76.471 1.721
430 CBF Yolk and CKF 30.556 76.364 1.718
431 HSS PBS and CKF 30.556 76.364 1.58
432 BQF PBS and CKF 30.556 76.364 1.617
433 KF PBS and SBF 42.222 76.316 1.761
434 CBF PBS and SBF 42.222 76.316 1.717
435 PBS CBF 44.444 76.25 1.492
436 CVF Yolk and CBF 25.556 76.087 2.536
437 PSF Yolk and CBF 25.556 76.087 2.14
438 KF Yolk and CBF 25.556 76.087 1.756
439 BQF Yolk 41.667 76 1.609
440 BQF TF and Yolk 13.889 76 1.609
441 KF CVF and BQF 27.778 76 1.754
442 PBS HSC and BQF 27.778 76 1.487
443 CBF HSC and BQF 27.778 76 1.455
444 KF CVF 30 75.926 1.752
445 HSC PSF and CBF 22.778 75.61 1.839
446 SBF HSC and HSS 22.778 75.61 1.479
69
447 CBF CKF 47.778 75.581 1.701
448 BQF CKF 47.778 75.581 1.601
449 HSC CVF and PSF 25 75.556 1.838
450 HSS BQF and CBF 31.667 75.439 1.561
451 CKF CBF and PBS 33.889 75.41 1.578
452 PSF CBF and CKF 36.111 75.385 2.12
453 BQF KF and CBF 36.111 75.385 1.596
454 CBF CBF and CKF 36.111 75.385 1.444
455 Yolk CF and CKF 11.111 75 1.8
456 Yolk CCF and BQF 17.778 75 1.8
457 CKF CCF and BQF 17.778 75 1.57
458 CKF TF and HSC 11.111 75 1.57
459 KF PSF and HSC 28.889 75 1.731
460 HSS HSC and CBF 24.444 75 1.552
461 HSS CBF and CBF 35.556 75 1.552
462 KF HSS and CBF 37.222 74.627 1.722
463 KF HSS and SBF 35 74.603 1.722
464 HSS HSC and PBS 26.111 74.468 1.541
465 KF CKF 47.778 74.419 1.717
466 CVF HSC and Yolk 23.889 74.419 2.481
467 KF HSC and Yolk 23.889 74.419 1.717
468 HSS CBF and SBF 45.556 74.39 1.539
469 KF CBF and SBF 45.556 74.39 1.717
470 CBF CBF and SBF 45.556 74.39 1.674
471 TF CCF 38.889 74.286 1.783
472 Yolk CCF and CKF 17.222 74.194 1.781
473 CKF TF and BQF 17.222 74.194 1.553
474 CKF PSF and HSS 15 74.074 1.55
475 SBF PSF and CKF 30 74.074 1.449
476 CBF SBF 51.111 73.913 1.663
477 TF CF and CBF 10.556 73.684 1.768
478 PBS CF and CBF 10.556 73.684 1.442
479 HSC KF and BQF 31.667 73.684 1.792
480 SBF Yolk and BQF 31.667 73.684 1.442
481 CBF PSF and BQF 29.444 73.585 1.409
482 BQF Yolk and HSS 18.889 73.529 1.557
483 KF CVF and Yolk 27.222 73.469 1.695
484 KF Yolk and SBF 27.222 73.469 1.695
485 KF PSF 35.556 73.438 1.695
486 SBF PSF 35.556 73.438 1.437
487 CKF Yolk 41.667 73.333 1.535
70
488 CBF CVF and PSF 25 73.333 1.404
489 CBF PSF and CBF 31.111 73.214 1.402
490 HSC CVF and KF 22.778 73.171 1.78
491 PBS CVF and KF 22.778 73.171 1.432
492 PBS Yolk and KF 22.778 73.171 1.432
493 BQF KF 43.333 73.077 1.548
494 SBF TF and PBS 14.444 73.077 1.43
495 SBF PSF and HSC 28.889 73.077 1.43
496 Yolk HSC and CKF 28.889 73.077 1.754
497 PBS HSC and CBF 28.889 73.077 1.43
498 CBF HSC and CBF 28.889 73.077 1.399
499 CBF HSS and SBF 35 73.016 1.643
500 CF CCF 38.889 72.857 2.522
501 CBF CCF and CVF 12.222 72.727 1.636
502 BQF HSS and CKF 24.444 72.727 1.54
503 HSC Yolk and CBF 28.333 72.549 1.765
504 SBF HSS 48.333 72.414 1.417
505 PBS TF and HSS 16.111 72.414 1.417
506 HSS CKF and CBF 32.222 72.414 1.498
507 CKF HSC and PBS 26.111 72.34 1.514
508 HSC CBF and CKF 36.111 72.308 1.759
509 HSC CBF and BQF 36.111 72.308 1.759
510 Yolk CKF and BQF 36.111 72.308 1.735
511 CVF TF and CBF 10 72.222 2.407
512 PSF TF and CBF 10 72.222 2.031
513 HSC TF and CBF 10 72.222 1.757
514 CBF TF and CBF 10 72.222 1.383
515 SBF CKF 47.778 72.093 1.411
516 SBF HSC and Yolk 23.889 72.093 1.411
517 Yolk HSC and BQF 27.778 72 1.728
518 CKF HSS and CBF 27.778 72 1.507
519 CF CCF and BQF 17.778 71.875 2.488
520 BQF TF and CKF 17.778 71.875 1.522
521 KF SBF 51.111 71.739 1.656
522 BQF SBF 51.111 71.739 1.519
523 KF PSF and Yolk 29.444 71.698 1.655
524 SBF PSF and Yolk 29.444 71.698 1.403
525 CBF HSS and CBF 37.222 71.642 1.612
526 CVF CCF and KF 11.667 71.429 2.381
527 PBS CCF and KF 11.667 71.429 1.398
528 BQF CCF and KF 11.667 71.429 1.513
71
529 CBF TF and KF 11.667 71.429 1.607
530 CVF Yolk and PBS 23.333 71.429 2.381
531 CBF CVF and Yolk 27.222 71.429 1.368
532 PSF Yolk and PBS 23.333 71.429 2.009
533 HSS Yolk and PBS 23.333 71.429 1.478
534 KF Yolk and PBS 23.333 71.429 1.648
535 CKF Yolk and SBF 27.222 71.429 1.495
536 BQF HSS and SBF 35 71.429 1.513
537 BQF KF and PBS 35 71.429 1.513
538 HSS CBF 52.222 71.277 1.475
539 HSS KF and SBF 36.667 71.212 1.473
540 Yolk HSC and CBF 28.889 71.154 1.708
541 KF PBS and CBF 46.111 71.084 1.64
542 BQF PBS and SBF 42.222 71.053 1.505
543 CCF TF and BQF 17.222 70.968 1.825
544 CVF CCF and CKF 17.222 70.968 2.366
545 CKF CF and BQF 13.333 70.833 1.483
546 KF HSS and PBS 40 70.833 1.635
547 CVF CKF and BQF 36.111 70.769 2.359
548 PSF CKF and BQF 36.111 70.769 1.99
549 Yolk CBF and BQF 36.111 70.769 1.698
550 PBS CBF and CKF 36.111 70.769 1.385
551 KF HSC and HSS 22.778 70.732 1.632
552 PSF Yolk 41.667 70.667 1.988
553 PBS CCF and CBF 18.889 70.588 1.381
554 PBS CVF and HSC 18.889 70.588 1.381
555 HSC CVF and PBS 18.889 70.588 1.717
556 CBF CVF and HSC 18.889 70.588 1.352
557 PSF HSC and CBF 24.444 70.455 1.982
558 CBF CVF 30 70.37 1.348
559 CCF TF and SBF 15 70.37 1.81
560 HSS TF and SBF 15 70.37 1.456
561 PBS TF and SBF 15 70.37 1.377
562 CKF TF and SBF 15 70.37 1.473
563 CVF PSF and HSS 15 70.37 2.346
564 HSC PBS and BQF 30 70.37 1.712
565 CVF PSF 35.556 70.312 2.344
566 PSF HSC 41.111 70.27 1.976
567 CBF HSC 41.111 70.27 1.581
568 CKF HSC 41.111 70.27 1.471
569 HSC CVF and CBF 26.111 70.213 1.708
72
570 PBS CVF and CBF 26.111 70.213 1.374
571 PBS PSF and KF 26.111 70.213 1.374
572 PSF CBF 44.444 70 1.969
573 CBF CVF and BQF 27.778 70 1.34 Table 2 Scoring for Rule Sets in All Regions
Sauced Beef Flavor Rule Set
Sauced Beef Flavor = 1.000 ID Probability Rule
34 1 IF Chives flavor = True and Pepper beef steak = True THEN 1.000 37 1 IF Pork steak = True and Pepper beef steak = True THEN 1.000 54 1 IF Pepper beef steak = True and BBQ flavor = True THEN 1.000 57 0.982 IF BBQ flavor = True and Curry beef = True THEN 1.000 41 0.976 IF Pork steak = True and Curry beef = True THEN 1.000 38 0.974 IF Chives flavor = True and Curry beef = True THEN 1.000 27 0.963 IF Pork steak = True and Hot & spices salt = True THEN 1.000 24 0.958 IF Chives flavor = True and Hot & spices salt = True THEN 1.000 46 0.957 IF Yolk = True and Curry beef = True THEN 1.000 47 0.957 IF Hot & spices salt = True and BBQ flavor = True THEN 1.000 44 0.955 IF Hot & spice sichuan = True and Curry beef = True THEN 1.000 64 0.953 IF Cumin BBQ = True and Curry beef = True THEN 1.000 42 0.952 IF Yolk = True and Pepper beef steak = True THEN 1.000 61 0.951 IF Cumin BBQ = True and Pepper beef steak = True THEN 1.000 19 0.947 IF Crab flavor = True and Curry beef = True THEN 1.000 65 0.938 IF Kimchi flavor = True and Curry beef = True THEN 1.000 58 0.931 IF Chicken flavor = True and Curry beef = True THEN 1.000 57 0.93 IF Kimchi flavor = True and BBQ flavor = True THEN 1.000 55 0.927 IF Pepper beef steak = True and Chicken flavor = True THEN 1.000 63 0.921 IF Kimchi flavor = True and Pepper beef steak = True THEN 1.000 50 0.92 IF Hot & spices salt = True and Cumin BBQ = True THEN 1.000 67 0.91 IF Hot & spices salt = True and Curry beef = True THEN 1.000 44 0.909 IF Hot & spices salt = True and Chicken flavor = True THEN 1.000 65 0.908 IF Cumin BBQ = True and BBQ flavor = True THEN 1.000vor 21 0.905 IF Cheese corn flavor = True and Kimchi flavor = True THEN 1.000 41 0.902 IF Chives flavor = True and Kimchi flavor = True THEN 1.000 50 0.9 IF Hot & spice sichuan = True and BBQ flavor = True THEN 1.000
Cumin BBQ Flavor Rule Set
Cumin BBQ Flavor = 1.000 ID Probability Rule
27 1 IF Pork steak = True and Hot & spices salt = True THEN 1.000 47 1 IF Pork steak = True and Kimchi flavor = True THEN 1.000
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37 1 IF Pork steak = True and Pepper beef steak = True THEN 1.000 41 1 IF Pork steak = True and Curry beef = True THEN 1.000 47 1 IF Pork steak = True and Sauced beef flavor = True THEN 1.000 57 0.982 IF Kimchi flavor = True and BBQ flavor = True THEN 1.000 43 0.977 IF Chives flavor = True and Sauced beef flavor = True THEN 1.000 41 0.976 IF Chives flavor = True and Kimchi flavor = True THEN 1.000 41 0.976 IF Yolk = True and Kimchi flavor = True THEN 1.000 38 0.974 IF Chives flavor = True and Curry beef = True THEN 1.000 34 0.971 IF Chives flavor = True and Hot & spice sichuan = True THEN 1.000 34 0.971 IF Chives flavor = True and Pepper beef steak = True THEN 1.000 53 0.962 IF Pork steak = True and BBQ flavor = True THEN 1.000 24 0.958 IF Chives flavor = True and Hot & spices salt = True THEN 1.000 48 0.958 IF Hot & spice sichuan = True and Kimchi flavor = True THEN 1.000 45 0.956 IF Chives flavor = True and Pork steak = True THEN 1.000 50 0.94 IF Hot & spice sichuan = True and BBQ flavor = True THEN 1.000 57 0.93 IF BBQ flavor = True and Curry beef = True THEN 1.000 54 0.926 IF Pepper beef steak = True and BBQ flavor = True THEN 1.000 49 0.918 IF Hot & spice sichuan = True and Sauced beef flavor = True THEN
1.000 54 0.907 IF Pork steak = True and Chicken flavor = True THEN 1.000 64 0.906 IF Kimchi flavor = True and Chicken flavor = True THEN 1.000 52 0.904 IF Hot&spice sichuan = True and Chicken flavor = True THEN 1.000
Pork Steak Flavor Rule Set
Pork Steak Flavor = 1.000 ID Probability Rule
34 1 IF Chives flavor = True and Hot&spice sichuan = True THEN 1.000 43 1 IF Hot&spice sichuan = True and Yolk = True THEN 1.000 41 0.927 IF Yolk = True and Kimchi flavor = True THEN 1.000 47 0.915 IF Chives flavor = True and Cumin BBQ = True THEN 1.000 41 0.902 IF Chives flavor = True and Kimchi flavor = True THEN 1.000 51 0.902 IF Yolk = True and Cumin BBQ = True THEN 1.000
Cheese Corn Flavor Rule Set
Cheese Corn Flavor = 1.000 ID Probability Rule
46 1 IF Crab flavor = True and Tomato flavor = True THEN 1.000 52 0.981 IF Crab flavor = True THEN 1.000 24 0.958 IF Crab flavor = True and BBQ flavor = True THEN 1.000 22 0.955 IF Crab flavor = True and Sauced beef flavor = True THEN 1.000 20 0.95 IF Crab flavor = True and Chicken flavor = True THEN 1.000 19 0.947 IF Crab flavor = True and Curry beef = True THEN 1.000
Tomato Flavor Rule Set
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Tomato Flavor = 1.000 ID Probability Rule
51 0.902 IF Crab flavor = True and Cheese corn flavor = True THEN 1.000 Chicken Flavor Rule Set
Chicken Flavor = 1.000 ID Probability Rule
22 1 IF Cheese corn flavor = True and Chives flavor = True THEN 1.000
18 1 IF Tomato flavor = True and Cumin BBQ = True THEN 1.000
34 0.971 IF Chives flavor = True and Hot & spice sichuan = True THEN 1.000
41 0.951 IF Chives flavor = True and Kimchi flavor = True THEN 1.000
45 0.933 IF Chives flavor = True and Pork steak = True THEN 1.000
50 0.92 IF Chives flavor = True and BBQ flavor = True THEN 1.000
47 0.915 IF Chives flavor = True and Cumin BBQ = True THEN 1.000
57 0.912 IF Kimchi flavor = True and BBQ flavor = True THEN 1.000
54 0.907 IF Chives flavor = True THEN 1.000
43 0.907 IF Chives flavor = True and Sauced beef flavor = True THEN 1.000
21 0.905 IF Cheese corn flavor = True and Kimchi flavor = True THEN 1.000
21 0.905 IF Tomato flavor = True and Kimchi flavor = True THEN 1.000
52 0.904 IF Hot & spice sichuan = True and Cumin BBQ = True THEN 1.000
Curry Beef Flavor Rule Set
Curry Beef Flavor = 1.000 ID Probability Rule
24 1 IF Cheese corn flavor = True and Pepper beef steak = True THEN 1.000
63 0.968 IF Hot & spices salt = True and Sauced beef flavor = True THEN 1.000
27 0.963 IF Pork steak = True and Hot & spices salt = True THEN 1.000
26 0.962 IF Tomato flavor = True and Pepper beef steak = True THEN 1.000
76 0.961 IF Pepper beef steak = True and Sauced beef flavor = True THEN 1.000
50 0.96 IF Hot & spices salt = True and Cumin BBQ = True THEN 1.000
24 0.958 IF Chives flavor = True and Hot & spices salt = True THEN 1.000
44 0.955 IF Hot & spices salt = True and Chicken flavor = True THEN 1.000
21 0.952 IF Cheese corn flavor = True and Kimchi flavor = True THEN 1.000
54 0.944 IF Pepper beef steak = True and BBQ flavor = True THEN 1.000
53 0.943 IF Hot & spices salt = True and Kimchi flavor = True THEN 1.000
63 0.937 IF Kimchi flavor = True and Pepper beef steak = True THEN 1.000
61 0.934 IF Cumin BBQ = True and Pepper beef steak = True THEN 1.000
42 0.929 IF Yolk = True and Pepper beef steak = True THEN 1.000
55 0.927 IF Pepper beef steak = True and Chicken flavor = True THEN 1.000
66 0.924 IF Kimchi flavor = True and Sauced beef flavor = True THEN 1.000
37 0.919 IF Pork steak = True and Pepper beef steak = True THEN 1.000
72 0.917 IF Hot & spices salt = True and Pepper beef steak = True THEN 1.000
47 0.915 IF Hot & spices salt = True and BBQ flavor = True THEN 1.000
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34 0.912 IF Chives flavor = True and Pepper beef steak = True THEN 1.000
21 0.905 IF Tomato flavor = True and Kimchi flavor = True THEN 1.000
92 0.902 IF Pepper beef steak = True THEN 1.000
Pepper Beef Steak Flavor Rule Set
Pepper Beef Steak Flavor = 1.000 ID Probability Rule
54 0.944 IF Pepper beef steak = True and BBQ flavor = True THEN 1.000
53 0.943 IF Hot & spices salt = True and Kimchi flavor = True THEN 1.000
63 0.937 IF Kimchi flavor = True and Pepper beef steak = True THEN 1.000
61 0.934 IF Cumin BBQ = True and Pepper beef steak = True THEN 1.000
42 0.929 IF Yolk = True and Pepper beef steak = True THEN 1.000
55 0.927 IF Pepper beef steak = True and Chicken flavor = True THEN 1.000
66 0.924 IF Kimchi flavor = True and Sauced beef flavor = True THEN 1.000
37 0.919 IF Pork steak = True and Pepper beef steak = True THEN 1.000
72 0.917 IF Hot & spices salt = True and Pepper beef steak = True THEN 1.000
47 0.915 IF Hot & spices salt = True and BBQ flavor = True THEN 1.000
34 0.912 IF Chives flavor = True and Pepper beef steak = True THEN 1.000
21 0.905 IF Tomato flavor = True and Kimchi flavor = True THEN 1.000
92 0.902 IF Pepper beef steak = True THEN PBS
Yolk Flavor Rule Set
Yolk Flavor = 1.000 ID Probability Rule
34 0.941 IF Chives flavor = True and Hot & spice sichuan = True THEN 1.000
45 0.933 IF Chives flavor = True and Pork steak = True THEN 1.000
38 0.921 IF Chives flavor = True and Curry beef = True THEN 1.000
50 0.92 IF Chives flavor = True and BBQ flavor = True THEN 1.000
47 0.915 IF Chives flavor = True and Cumin BBQ = True THEN 1.000
22 0.909 IF Cheese corn flavor = True and Chives flavor = True THEN 1.000
54 0.907 IF Chives flavor = True THEN 1.000
BBQ Flavor Rule Set
BBQ Flavor = 1.000 ID Probability Rule
47 0.936 IF Chives flavor = True and Cumin BBQ = True THEN 1.000
47 0.936 IF Pork steak = True and Kimchi flavor = True THEN 1.000
45 0.933 IF Chives flavor = True and Pork steak = True THEN 1.000
43 0.93 IF Chives flavor = True and Sauced beef flavor = True THEN 1.000
41 0.927 IF Chives flavor = True and Kimchi flavor = True THEN 1.000
41 0.927 IF Yolk = True and Kimchi flavor = True THEN 1.000
54 0.926 IF Chives flavor = True THEN 1.000
26 0.923 IF Cheese corn flavor = True and Yolk = True THEN 1.000
38 0.921 IF Chives flavor = True and Curry beef = True THEN 1.000
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49 0.918 IF Hot&spice sichuan = True and Sauced beef flavor = True THEN 1.000
24 0.917 IF Chives flavor = True and Hot & spices salt = True THEN 1.000
56 0.911 IF Pork steak = True and Cumin BBQ = True THEN 1.000
22 0.909 IF Cheese corn flavor = True and Chives flavor = True THEN 1.000
52 0.904 IF Hot&spice sichuan = True and Cumin BBQ = True THEN 1.000
51 0.902 IF Yolk = True and Cumin BBQ = True THEN 1.000
Kimchi Flavor Rule Set
Kimchi Flavor = 1.000 ID Probability Rule
41 0.902 IF Pork steak = True and Curry beef = True THEN 1.000
44 0.932 IF Hot & spices salt = True and Chicken flavor = True THEN 1.000
55 0.909 IF Pepper beef steak = True and Chicken flavor = True THEN 1.000
58 0.914 IF Chicken flavor = True and Curry beef = True THEN 1.000
62 0.903 IF Chicken flavor = True and Sauced beef flavor = True THEN 1.000 Table 3 Scoring information for Top 10 Rules in All Regions Year 13 14 15 14 15 13 15 13 14 13 North South Mid East SW Jan. May Sep. Jan. May. Sep. Jan. May. Sep. Jan. TF 1 0 0 1 1 0 0 1 1 1 CF 0 0 0 1 1 0 0 1 1 0 SBF 1 1 1 0 0 1 1 1 1 0 CCF 0 0 1 1 1 0 0 1 1 0 BQF 0 0 1 0 1 1 1 0 1 0 PBS 1 1 1 0 0 1 1 0 1 0 CKF 1 0 1 0 0 1 1 0 1 0 CBF 1 1 1 0 0 1 1 1 1 0 CBQ 1 1 1 0 0 1 1 0 1 0 HSS 1 1 1 0 0 1 0 0 1 1 PSF 0 0 1 0 0 1 1 0 0 0 YF 0 0 1 0 0 1 1 0 0 0 KF 1 1 1 0 0 1 1 0 1 0 CVF 0 0 1 0 0 1 1 0 1 0 HSC 0 0 1 0 0 0 1 0 0 0
Scoring Information Prediction 1 CF PBS CBQ CCF CCF CBQ CBQ CCF CCF PBS Confidence 1 1 0.99 1 1 1 1 1 1 1 0.83 Rule ID 1 14 15 2 4 4 2 2 4 4 306
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Prediction 2 PBS CBF CBF CCF CCF SBF SBF CCF CKF Confidence 2 0.99 0.97 1 0.98 0.98 1 1 0.98 1 Rule ID 2 15 30 12 18 18 1 1 18 14 Prediction 3 CBF PBF CKF TF CCF SBF SBF CCF CBF Confidence 3 0.99 0.96 1 0.90 0.96 1 1 0.96 1 Rule ID 3 30 35 13 139 41 7 7 52 12 Table 4 Results for the North China Region
Consequent Antecedent Support % Confidence % Lift
1 CVF YF 36.111 100 2.25 2 CF YF and HSS 11.111 100 2.118 3 TF YF and HSS 11.111 100 2.118 4 CBF YF and HSS 11.111 100 1.895 5 PBS YF and HSS 11.111 100 2 6 CVF YF and HSS 11.111 100 2.25 7 CCF YF and HSS 11.111 100 2.118 8 SBF YF and HSS 11.111 100 1.8 9 KF YF and HSS 11.111 100 1.636
10 PSF YF and CKF 30.556 100 2.571 11 CBF YF and PSF 33.333 100 2.571 12 PSF YF and CBF 33.333 100 2.571 13 CVF YF and PSF 33.333 100 2.25 14 PSF YF and HSC 30.556 100 2.571 15 BQF YF and PSF 33.333 100 2.25 16 PSF YF and BQF 33.333 100 2.571 17 CBF YF and CKF 30.556 100 2.571 18 CVF YF and CKF 30.556 100 2.25 19 BQF YF and CKF 30.556 100 2.25 20 CCF YF and CKF 30.556 100 2.118 21 CVF YF and CBF 33.333 100 2.25 22 CBF YF and HSC 30.556 100 2.571 23 BQF YF and CBF 33.333 100 2.25 24 CBF YF and BQF 33.333 100 2.571 25 CF YF and CBF 16.667 100 2.118 26 CF YF and PBS 19.444 100 2.118 27 CVF YF and CF 27.778 100 2.25 28 CVF YF and TF 22.222 100 2.25 29 CCF YF and TF 22.222 100 2.118 30 PBS YF and CBF 16.667 100 2 31 CVF YF and CBF 16.667 100 2.25 32 CCF YF and CBF 16.667 100 2.118 33 SBF YF and CBF 16.667 100 1.8
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34 KF YF and CBF 16.667 100 1.636 35 CVF YF and PBS 19.444 100 2.25 36 CCF YF and PBS 19.444 100 2.118 37 SBF YF and PBS 19.444 100 1.8 38 KF YF and PBS 19.444 100 1.636 39 CVF YF and HSC 30.556 100 2.25 40 CVF YF and BQF 33.333 100 2.25 41 CVF YF and CCF 33.333 100 2.25 42 CVF YF and SBF 27.778 100 2.25 43 CVF YF and KF 27.778 100 2.25 44 BQF YF and HSC 30.556 100 2.25 45 CCF YF and KF 27.778 100 2.118 46 CKF HSS and PSF 11.111 100 2.571 47 CBF HSS and PSF 11.111 100 2.571 48 CF HSS and PSF 11.111 100 2.118 49 TF HSS and PSF 11.111 100 2.118 50 CBF HSS and PSF 11.111 100 1.895 51 PBS HSS and PSF 11.111 100 2 52 CVF HSS and PSF 11.111 100 2.25 53 BQF HSS and PSF 11.111 100 2.25 54 CCF HSS and PSF 11.111 100 2.118 55 SBF HSS and PSF 11.111 100 1.8 56 KF HSS and PSF 11.111 100 1.636 57 CBF HSS and CKF 16.667 100 1.895 58 PBS HSS and CKF 16.667 100 2 59 KF HSS and CKF 16.667 100 1.636 60 CF HSS and CBF 13.889 100 2.118 61 TF HSS and CBF 13.889 100 2.118 62 CBF HSS and CBF 13.889 100 1.895 63 PBS HSS and CBF 13.889 100 2 64 CCF HSS and CBF 13.889 100 2.118 65 SBF HSS and CBF 13.889 100 1.8 66 KF HSS and CBF 13.889 100 1.636 67 CBF HSS and CF 25 100 1.895 68 KF HSS and CF 25 100 1.636 69 TF HSS and BQF 19.444 100 2.118 70 CBF HSS and CVF 19.444 100 1.895 71 CBF HSS and BQF 19.444 100 1.895 72 CBF HSS and CCF 25 100 1.895 73 CBF HSS and SBF 36.111 100 1.895 74 CBF HSS and KF 44.444 100 1.895
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75 PBS HSS and HSC 22.222 100 2 76 PBS HSS and BQF 19.444 100 2 77 PBS HSS and CCF 25 100 2 78 SBF HSS and CVF 19.444 100 1.8 79 SBF HSS and BQF 19.444 100 1.8 80 KF HSS and BQF 19.444 100 1.636 81 SBF HSS and CCF 25 100 1.8 82 KF HSS and CCF 25 100 1.636 83 CBF PSF and CKF 33.333 100 2.571 84 PSF CKF and CBF 33.333 100 2.571 85 PSF CKF and CF 25 100 2.571 86 CKF PSF and TF 22.222 100 2.571 87 CKF PSF and CBF 16.667 100 2.571 88 CKF PSF and PBS 19.444 100 2.571 89 CVF PSF and CKF 33.333 100 2.25 90 PSF CKF and CVF 33.333 100 2.571 91 BQF PSF and CKF 33.333 100 2.25 92 CCF PSF and CKF 33.333 100 2.118 93 CKF PSF and CCF 33.333 100 2.571 94 CKF PSF and KF 27.778 100 2.571 95 CBF PSF and CF 27.778 100 2.571 96 CBF PSF and TF 22.222 100 2.571 97 CBF PSF and CBF 16.667 100 2.571 98 CBF PSF and PBS 19.444 100 2.571 99 CVF PSF and CBF 36.111 100 2.25
100 CBF PSF and CVF 36.111 100 2.571 101 PSF CBF and CVF 36.111 100 2.571 102 CBF PSF and HSC 33.333 100 2.571 103 BQF PSF and CBF 36.111 100 2.25 104 CBF PSF and BQF 36.111 100 2.571 105 PSF CBF and BQF 36.111 100 2.571 106 CBF PSF and CCF 33.333 100 2.571 107 CBF PSF and SBF 27.778 100 2.571 108 CBF PSF and KF 27.778 100 2.571 109 CF PSF and CBF 16.667 100 2.118 110 CF PSF and PBS 19.444 100 2.118 111 CVF PSF and CF 27.778 100 2.25 112 BQF PSF and CF 27.778 100 2.25 113 PSF CF and BQF 27.778 100 2.571 114 CVF PSF and TF 22.222 100 2.25 115 BQF PSF and TF 22.222 100 2.25
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116 CCF PSF and TF 22.222 100 2.118 117 PBS PSF and CBF 16.667 100 2 118 CVF PSF and CBF 16.667 100 2.25 119 BQF PSF and CBF 16.667 100 2.25 120 CCF PSF and CBF 16.667 100 2.118 121 SBF PSF and CBF 16.667 100 1.8 122 KF PSF and CBF 16.667 100 1.636 123 CVF PSF and PBS 19.444 100 2.25 124 BQF PSF and PBS 19.444 100 2.25 125 CCF PSF and PBS 19.444 100 2.118 126 SBF PSF and PBS 19.444 100 1.8 127 KF PSF and PBS 19.444 100 1.636 128 CVF PSF and HSC 33.333 100 2.25 129 PSF CVF and HSC 33.333 100 2.571 130 BQF PSF and CVF 36.111 100 2.25 131 CVF PSF and BQF 36.111 100 2.25 132 PSF CVF and BQF 36.111 100 2.571 133 CVF PSF and CCF 33.333 100 2.25 134 CVF PSF and SBF 27.778 100 2.25 135 CVF PSF and KF 27.778 100 2.25 136 BQF PSF and HSC 33.333 100 2.25 137 BQF PSF and CCF 33.333 100 2.25 138 BQF PSF and SBF 27.778 100 2.25 139 BQF PSF and KF 27.778 100 2.25 140 CCF PSF and KF 27.778 100 2.118 141 CBF CKF and CF 25 100 2.571 142 CVF CKF and CBF 33.333 100 2.25 143 CBF CKF and CVF 33.333 100 2.571 144 BQF CKF and CBF 33.333 100 2.25 145 CCF CKF and CBF 33.333 100 2.118 146 CVF CKF and CF 25 100 2.25 147 BQF CKF and CF 25 100 2.25 148 CCF CKF and CF 25 100 2.118 149 BQF CKF and TF 25 100 2.25 150 CCF CKF and TF 25 100 2.118 151 PBS CKF and CBF 22.222 100 2 152 KF CKF and CBF 22.222 100 1.636 153 KF CKF and PBS 25 100 1.636 154 BQF CKF and CVF 33.333 100 2.25 155 CCF CKF and CVF 33.333 100 2.118 156 BQF CKF and HSC 33.333 100 2.25
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157 CCF CKF and HSC 33.333 100 2.118 158 CCF CKF and BQF 36.111 100 2.118 159 BQF CKF and CCF 36.111 100 2.25 160 BQF CKF and SBF 27.778 100 2.25 161 CCF CKF and SBF 27.778 100 2.118 162 CF CBF and CBF 19.444 100 2.118 163 CF CBF and PBS 22.222 100 2.118 164 CBF CF and BQF 27.778 100 2.571 165 CCF CBF and TF 25 100 2.118 166 PBS CBF and CBF 19.444 100 2 167 CCF CBF and CBF 19.444 100 2.118 168 SBF CBF and CBF 19.444 100 1.8 169 KF CBF and CBF 19.444 100 1.636 170 CCF CBF and PBS 22.222 100 2.118 171 SBF CBF and PBS 22.222 100 1.8 172 KF CBF and PBS 22.222 100 1.636 173 CBF CVF and HSC 33.333 100 2.571 174 BQF CBF and CVF 36.111 100 2.25 175 CVF CBF and BQF 36.111 100 2.25 176 CBF CVF and BQF 36.111 100 2.571 177 CCF CBF and KF 30.556 100 2.118 178 PBS CF and TF 25 100 2 179 KF CF and TF 25 100 1.636 180 KF CF and CBF 30.556 100 1.636 181 CF PBS and CVF 22.222 100 2.118 182 KF CF and PBS 30.556 100 1.636 183 CVF CF and BQF 27.778 100 2.25 184 KF TF and PBS 36.111 100 1.636 185 PBS CBF and HSC 25 100 2 186 PBS CBF and BQF 25 100 2 187 PBS CBF and CCF 30.556 100 2 188 KF CBF and PBS 44.444 100 1.636 189 SBF CBF and CVF 25 100 1.8 190 SBF CBF and HSC 25 100 1.8 191 KF CBF and HSC 25 100 1.636 192 SBF CBF and BQF 25 100 1.8 193 KF CBF and BQF 25 100 1.636 194 SBF CBF and CCF 30.556 100 1.8 195 KF CBF and CCF 30.556 100 1.636 196 CCF PBS and CVF 22.222 100 2.118 197 SBF PBS and CVF 22.222 100 1.8
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198 KF PBS and CVF 22.222 100 1.636 199 SBF PBS and BQF 27.778 100 1.8 200 KF PBS and BQF 27.778 100 1.636 201 SBF PBS and CCF 33.333 100 1.8 202 KF PBS and CCF 33.333 100 1.636 203 KF PBS and SBF 38.889 100 1.636 204 BQF CVF and HSC 33.333 100 2.25 205 KF CBF 52.778 94.737 1.55 206 KF PBS 50 94.444 1.545 207 KF HSS and CBF 47.222 94.118 1.54 208 CBF PBS and KF 47.222 94.118 1.783 209 CBF HSS and PBS 41.667 93.333 1.768 210 KF HSS and PBS 41.667 93.333 1.527 211 KF CBF and SBF 41.667 93.333 1.527 212 CBF PSF 38.889 92.857 2.388 213 PSF CBF 38.889 92.857 2.388 214 CVF PSF 38.889 92.857 2.089 215 BQF PSF 38.889 92.857 2.089 216 BQF CKF 38.889 92.857 2.089 217 CCF CKF 38.889 92.857 1.966 218 CVF CBF 38.889 92.857 2.089 219 HSC CBF 38.889 92.857 1.966 220 BQF CBF 38.889 92.857 2.089 221 CCF CBF 38.889 92.857 1.966 222 CKF BQF and CCF 38.889 92.857 2.388 223 PBS TF and KF 38.889 92.857 1.857 224 CBF PBS and SBF 38.889 92.857 1.759 225 KF CCF and SBF 38.889 92.857 1.519 226 PSF YF 36.111 92.308 2.374 227 CBF YF 36.111 92.308 2.374 228 BQF YF 36.111 92.308 2.077 229 CCF YF 36.111 92.308 1.955 230 YF PSF and CBF 36.111 92.308 2.556 231 PSF YF and CVF 36.111 92.308 2.374 232 YF PSF and CVF 36.111 92.308 2.556 233 YF PSF and BQF 36.111 92.308 2.556 234 CBF YF and CVF 36.111 92.308 2.374 235 YF CBF and CVF 36.111 92.308 2.556 236 YF CBF and BQF 36.111 92.308 2.556 237 BQF YF and CVF 36.111 92.308 2.077 238 YF CVF and BQF 36.111 92.308 2.556
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239 CCF YF and CVF 36.111 92.308 1.955 240 YF CVF and CCF 36.111 92.308 2.556 241 CBF HSS and TF 36.111 92.308 1.749 242 HSS TF and CBF 36.111 92.308 1.749 243 KF HSS and SBF 36.111 92.308 1.51 244 CKF PSF and CBF 36.111 92.308 2.374 245 CKF PSF and CVF 36.111 92.308 2.374 246 CKF PSF and BQF 36.111 92.308 2.374 247 PSF CKF and BQF 36.111 92.308 2.374 248 PSF CKF and CCF 36.111 92.308 2.374 249 HSC PSF and CBF 36.111 92.308 1.955 250 PSF CBF and HSC 36.111 92.308 2.374 251 CCF PSF and CBF 36.111 92.308 1.955 252 PSF CBF and CCF 36.111 92.308 2.374 253 HSC PSF and CVF 36.111 92.308 1.955 254 CCF PSF and CVF 36.111 92.308 1.955 255 PSF CVF and CCF 36.111 92.308 2.374 256 HSC PSF and BQF 36.111 92.308 1.955 257 CCF PSF and BQF 36.111 92.308 1.955 258 CKF CBF and CVF 36.111 92.308 2.374 259 CBF CKF and BQF 36.111 92.308 2.374 260 CKF CBF and BQF 36.111 92.308 2.374 261 CBF CKF and CCF 36.111 92.308 2.374 262 CKF CBF and CCF 36.111 92.308 2.374 263 CVF CKF and BQF 36.111 92.308 2.077 264 CKF CVF and BQF 36.111 92.308 2.374 265 CVF CKF and CCF 36.111 92.308 2.077 266 CKF CVF and CCF 36.111 92.308 2.374 267 HSC CKF and BQF 36.111 92.308 1.955 268 HSC CKF and CCF 36.111 92.308 1.955 269 HSC CBF and CVF 36.111 92.308 1.955 270 CVF CBF and HSC 36.111 92.308 2.077 271 CCF CBF and CVF 36.111 92.308 1.955 272 CVF CBF and CCF 36.111 92.308 2.077 273 CBF CVF and CCF 36.111 92.308 2.374 274 BQF CBF and HSC 36.111 92.308 2.077 275 HSC CBF and BQF 36.111 92.308 1.955 276 CCF CBF and HSC 36.111 92.308 1.955 277 HSC CBF and CCF 36.111 92.308 1.955 278 CCF CBF and BQF 36.111 92.308 1.955 279 BQF CBF and CCF 36.111 92.308 2.077
84
280 PBS TF and CBF 36.111 92.308 1.846 281 CBF TF and PBS 36.111 92.308 1.749 282 KF TF and CBF 36.111 92.308 1.51 283 HSC CVF and BQF 36.111 92.308 1.955 284 CCF CVF and BQF 36.111 92.308 1.955 285 BQF CVF and CCF 36.111 92.308 2.077 286 CCF HSC and KF 36.111 92.308 1.955 287 CCF BQF and KF 36.111 92.308 1.955 288 CKF YF and PSF 33.333 91.667 2.357 289 YF PSF and CKF 33.333 91.667 2.538 290 HSC YF and PSF 33.333 91.667 1.941 291 YF PSF and HSC 33.333 91.667 2.538 292 CCF YF and PSF 33.333 91.667 1.941 293 PSF YF and CCF 33.333 91.667 2.357 294 YF PSF and CCF 33.333 91.667 2.538 295 CKF YF and CBF 33.333 91.667 2.357 296 YF CKF and CBF 33.333 91.667 2.538 297 YF CKF and CVF 33.333 91.667 2.538 298 CKF YF and BQF 33.333 91.667 2.357 299 CKF YF and CCF 33.333 91.667 2.357 300 HSC YF and CBF 33.333 91.667 1.941 301 CCF YF and CBF 33.333 91.667 1.941 302 CBF YF and CCF 33.333 91.667 2.357 303 YF CVF and HSC 33.333 91.667 2.538 304 HSC YF and BQF 33.333 91.667 1.941 305 CCF YF and BQF 33.333 91.667 1.941 306 BQF YF and CCF 33.333 91.667 2.062 307 HSC PSF and CKF 33.333 91.667 1.941 308 CKF PSF and HSC 33.333 91.667 2.357 309 PSF CKF and HSC 33.333 91.667 2.357 310 CCF PSF and HSC 33.333 91.667 1.941 311 HSC PSF and CCF 33.333 91.667 1.941 312 HSC CKF and CBF 33.333 91.667 1.941 313 CBF CKF and HSC 33.333 91.667 2.357 314 HSC CKF and CVF 33.333 91.667 1.941 315 CVF CKF and HSC 33.333 91.667 2.062 316 CKF CVF and HSC 33.333 91.667 2.357 317 BQF CKF and KF 33.333 91.667 2.062 318 CCF CKF and KF 33.333 91.667 1.941 319 KF CF and CCF 33.333 91.667 1.5 320 KF CF and SBF 33.333 91.667 1.5
85
321 SBF TF and CCF 33.333 91.667 1.65 322 KF TF and CCF 33.333 91.667 1.5 323 CBF PBS and CCF 33.333 91.667 1.737 324 CCF CVF and HSC 33.333 91.667 1.941 325 CCF CVF and KF 33.333 91.667 1.941 326 HSC YF and CKF 30.556 90.909 1.925 327 CKF YF and HSC 30.556 90.909 2.338 328 CCF YF and HSC 30.556 90.909 1.925 329 PSF CBF and CF 30.556 90.909 2.338 330 PSF CBF and SBF 30.556 90.909 2.338 331 PSF CBF and KF 30.556 90.909 2.338 332 CKF CBF and KF 30.556 90.909 2.338 333 CVF CBF and CF 30.556 90.909 2.045 334 HSC CBF and CF 30.556 90.909 1.925 335 CBF CF and HSC 30.556 90.909 2.338 336 BQF CBF and CF 30.556 90.909 2.045 337 CCF CBF and CF 30.556 90.909 1.925 338 CVF CBF and SBF 30.556 90.909 2.045 339 CVF CBF and KF 30.556 90.909 2.045 340 HSC CBF and SBF 30.556 90.909 1.925 341 HSC CBF and KF 30.556 90.909 1.925 342 BQF CBF and SBF 30.556 90.909 2.045 343 BQF CBF and KF 30.556 90.909 2.045 344 CCF CBF and SBF 30.556 90.909 1.925 345 PBS CF and CBF 30.556 90.909 1.818 346 CBF CF and PBS 30.556 90.909 1.722 347 SBF CF and CBF 30.556 90.909 1.636 348 CCF CF and PBS 30.556 90.909 1.925 349 SBF CF and PBS 30.556 90.909 1.636 350 CCF CF and HSC 30.556 90.909 1.925 351 CCF TF and BQF 30.556 90.909 1.925 352 SBF TF and BQF 30.556 90.909 1.636 353 KF TF and BQF 30.556 90.909 1.488 354 SBF PBS and HSC 30.556 90.909 1.636 355 KF PBS and HSC 30.556 90.909 1.488 356 PSF YF and CF 27.778 90 2.314 357 YF PSF and CF 27.778 90 2.492 358 PSF YF and SBF 27.778 90 2.314 359 YF PSF and SBF 27.778 90 2.492 360 PSF YF and KF 27.778 90 2.314 361 YF PSF and KF 27.778 90 2.492
86
362 CKF YF and KF 27.778 90 2.314 363 CBF YF and CF 27.778 90 2.314 364 CBF YF and SBF 27.778 90 2.314 365 CBF YF and KF 27.778 90 2.314 366 BQF YF and CF 27.778 90 2.025 367 YF CF and BQF 27.778 90 2.492 368 CCF YF and CF 27.778 90 1.906 369 BQF YF and SBF 27.778 90 2.025 370 BQF YF and KF 27.778 90 2.025 371 CCF YF and SBF 27.778 90 1.906 372 CKF PSF and CF 27.778 90 2.314 373 CKF PSF and SBF 27.778 90 2.314 374 PSF CKF and SBF 27.778 90 2.314 375 HSC PSF and CF 27.778 90 1.906 376 CCF PSF and CF 27.778 90 1.906 377 HSC PSF and SBF 27.778 90 1.906 378 HSC PSF and KF 27.778 90 1.906 379 CCF PSF and SBF 27.778 90 1.906 380 CBF CKF and SBF 27.778 90 2.314 381 CKF CF and BQF 27.778 90 2.314 382 CVF CKF and SBF 27.778 90 2.025 383 HSC CKF and SBF 27.778 90 1.906 384 KF CKF and SBF 27.778 90 1.473 385 HSC CF and BQF 27.778 90 1.906 386 CCF CF and BQF 27.778 90 1.906 387 TF PBS and BQF 27.778 90 1.906 388 CCF TF and CVF 27.778 90 1.906 389 SBF TF and CVF 27.778 90 1.62 390 BQF TF and HSC 27.778 90 2.025 391 CCF TF and HSC 27.778 90 1.906 392 SBF TF and HSC 27.778 90 1.62 393 KF TF and HSC 27.778 90 1.473 394 CBF PBS and BQF 27.778 90 1.705 395 CCF PBS and BQF 27.778 90 1.906 Table 5 Scoring for All Rule Sets in the North China
Cheese Corn Flavor Rule Set
Cheese Corn Flavor = 1.000
ID Probability Rule
10 1 IF Yolk = True and Crab flavor = True then 1.000
10 1 IF Yolk = True and Sauced beef flavor = True then 1.000
10 1 IF Pork steak = True and Crab flavor = True then 1.000
87
10 1 IF Pork steak = True and Sauced beef flavor = True then 1.000
10 1 IF Crab flavor = True and BBQ flavor = True then 1.000
10 1 IF Tomato flavor = True and Chives flavor = True then 1.000
10 1 IF Tomato flavor = True and Hot sichuan = True then 1.000
10 1 IF Pepper beef steak = True and BBQ flavor = True then 1.000
11 1 IF Yolk = True and Hot sichuan = True then 1.000
11 1 IF Cumin BBQ = True and Crab flavor = True then 1.000
11 1 IF Cumin BBQ = True and Sauced beef flavor = True then 1.000
11 1 IF Crab flavor = True and Pepper beef steak = True then 1.000
11 1 IF Crab flavor = True and Hot sichuan = True then 1.000
11 1 IF Tomato flavor = True and BBQ flavor = True then 1.000
12 1 IF Yolk = True and Pork steak = True then 1.000
12 1 IF Yolk = True and Cumin BBQ = True then 1.000
12 1 IF Yolk = True and BBQ flavor = True then 1.000
12 1 IF Pork steak = True and Hot sichuan = True then 1.000
12 1 IF Chicken flavor = True and Kimchi flavor = True then 1.000
12 1 IF Chives flavor = True and Hot sichuan = True then 1.000
12 1 IF Chives flavor = True and Kimchi flavor = True then 1.000
13 1 IF Yolk = True then 1.000
13 1 IF Yolk = True and Chives flavor = True then 1.000
13 1 IF Pork steak = True and Cumin BBQ = True then 1.000
13 1 IF Pork steak = True and Chives flavor = True then 1.000
13 0.929 IF Pork steak = True and BBQ flavor = True then 1.000
13 0.929 IF Cumin BBQ = True and Chives flavor = True then 1.000
13 0.923 IF Cumin BBQ = True and Hot sichuan = True then 1.000
13 0.923 IF Cumin BBQ = True and BBQ flavor = True then 1.000
13 0.923 IF Chives flavor = True and BBQ flavor = True then 1.000
13 0.923 IF Hot sichuan = True and Kimchi flavor = True then 1.000
13 0.923 IF BBQ flavor = True and Kimchi flavor = True then 1.000
14 0.923 IF Chicken flavor = True then 1.000
14 0.923 IF Cumin BBQ = True then 1.000
4 0.923 IF Yolk = True and spices salt = True then 1.000
11 0.923 IF Yolk = True and Chicken flavor = True then 1.000
8 0.923 IF Yolk = True and Tomato flavor = True then 1.000
6 0.923 IF Yolk = True and Curry beef = True then 1.000
7 0.917 IF Yolk = True and Pepper beef steak = True then 1.000
10 0.917 IF Yolk = True and Kimchi flavor = True then 1.000
4 0.917 IF spices salt = True and Pork steak = True then 1.000
5 0.917 IF spices salt = True and Cumin BBQ = True then 1.000
12 0.917 IF Pork steak = True and Chicken flavor = True then 1.000
8 0.917 IF Pork steak = True and Tomato flavor = True then 1.000
88
6 0.917 IF Pork steak = True and Curry beef = True then 1.000
7 0.909 IF Pork steak = True and Pepper beef steak = True then 1.000
10 0.909 IF Pork steak = True and Kimchi flavor = True then 1.000
12 0.909 IF Chicken flavor = True and Cumin BBQ = True then 1.000
9 0.909 IF Chicken flavor = True and Crab flavor = True then 1.000
9 0.909 IF Chicken flavor = True and Tomato flavor = True then 1.000
12 0.909 IF Chicken flavor = True and Chives flavor = True then 1.000
12 0.9 IF Chicken flavor = True and Hot sichuan = True then 1.000
13 0.9 IF Chicken flavor = True and BBQ flavor = True then 1.000
10 0.9 IF Chicken flavor = True and Sauced beef flavor = True then 1.000
9 0.9 IF Cumin BBQ = True and Tomato flavor = True then 1.000
7 0.9 IF Cumin BBQ = True and Curry beef = True then 1.000
8 0.9 IF Cumin BBQ = True and Pepper beef steak = True then 1.000
11 0.9 IF Cumin BBQ = True and Kimchi flavor = True then 1.000
8 0.9 IF Pepper beef steak = True and Chives flavor = True then 1.000
Kimchi Flavor Rule Set
Kimchi Flavor = 1.000
ID Probability Rule
4 1 IF Yolk = True and spices salt = True then 1.000
6 1 IF Yolk = True and Curry beef = True then 1.000
7 1 IF Yolk = True and Pepper beef steak = True then 1.000
4 1 IF spices salt = True and Pork steak = True then 1.000
6 1 IF spices salt = True and Chicken flavor = True then 1.000
5 1 IF spices salt = True and Cumin BBQ = True then 1.000
9 1 IF spices salt = True and Crab flavor = True then 1.000
7 1 IF spices salt = True and BBQ flavor = True then 1.000
9 1 IF spices salt = True and Cheese corn flavor = True then 1.000
6 1 IF Pork steak = True and Curry beef = True then 1.000
7 1 IF Pork steak = True and Pepper beef steak = True then 1.000
8 1 IF Chicken flavor = True and Curry beef = True then 1.000
9 1 IF Chicken flavor = True and Pepper beef steak = True then 1.000
7 1 IF Cumin BBQ = True and Curry beef = True then 1.000
8 1 IF Cumin BBQ = True and Pepper beef steak = True then 1.000
9 1 IF Crab flavor = True and Tomato flavor = True then 1.000
11 1 IF Crab flavor = True and Curry beef = True then 1.000
11 1 IF Crab flavor = True and Pepper beef steak = True then 1.000
13 1 IF Tomato flavor = True and Pepper beef steak = True then 1.000
16 1 IF Curry beef = True and Pepper beef steak = True then 1.000
9 1 IF Curry beef = True and Hot sichuan = True then 1.000
9 1 IF Curry beef = True and BBQ flavor = True then 1.000
11 1 IF Curry beef = True and Cheese corn flavor = True then 1.000
89
8 1 IF Pepper beef steak = True and Chives flavor = True then 1.000
10 1 IF Pepper beef steak = True and BBQ flavor = True then 1.000
12 1 IF Pepper beef steak = True and Cheese corn flavor = True then 1.000
14 1 IF Pepper beef steak = True and Sauced beef flavor = True then 1.000
19 0.947 IF Curry beef = True then 1.000
18 0.944 IF Pepper beef steak = True then 1.000
17 0.941 IF spices salt = True and Curry beef = True then 1.000
15 0.933 IF spices salt = True and Pepper beef steak = True then 1.000
15 0.933 IF Curry beef = True and Sauced beef flavor = True then 1.000
14 0.929 IF Cheese corn flavor = True and Sauced beef flavor = True then 1.000
13 0.923 IF spices salt = True and Sauced beef flavor = True then 1.000
13 0.923 IF Tomato flavor = True and Curry beef = True then 1.000
12 0.917 IF Crab flavor = True and Cheese corn flavor = True then 1.000
12 0.917 IF Crab flavor = True and Sauced beef flavor = True then 1.000
12 0.917 IF Tomato flavor = True and Cheese corn flavor = True then 1.000
11 0.909 IF Tomato flavor = True and BBQ flavor = True then 1.000
11 0.909 IF Pepper beef steak = True and Hot sichuan = True then 1.000
10 0.9 IF Chicken flavor = True and Sauced beef flavor = True then 1.000
10 0.9 IF Tomato flavor = True and Hot sichuan = True then 1.000
BBQ Flavor Rule Set
BBQ Flavor = 1.000
ID Probability Rule
12 1 IF Yolk = True and Pork steak = True then 1.000
11 1 IF Yolk = True and Chicken flavor = True then 1.000
12 1 IF Yolk = True and Cumin BBQ = True then 1.000
11 1 IF Yolk = True and Hot sichuan = True then 1.000
4 1 IF spices salt = True and Pork steak = True then 1.000
12 1 IF Pork steak = True and Chicken flavor = True then 1.000
13 1 IF Pork steak = True and Cumin BBQ = True then 1.000
10 1 IF Pork steak = True and Crab flavor = True then 1.000
8 1 IF Pork steak = True and Tomato flavor = True then 1.000
6 1 IF Pork steak = True and Curry beef = True then 1.000
7 1 IF Pork steak = True and Pepper beef steak = True then 1.000
13 1 IF Pork steak = True and Chives flavor = True then 1.000
12 1 IF Pork steak = True and Hot sichuan = True then 1.000
12 1 IF Pork steak = True and Cheese corn flavor = True then 1.000
10 1 IF Pork steak = True and Sauced beef flavor = True then 1.000
10 1 IF Pork steak = True and Kimchi flavor = True then 1.000
12 1 IF Chicken flavor = True and Cumin BBQ = True then 1.000
9 1 IF Chicken flavor = True and Crab flavor = True then 1.000
9 1 IF Chicken flavor = True and Tomato flavor = True then 1.000
90
12 1 IF Chicken flavor = True and Chives flavor = True then 1.000
12 1 IF Chicken flavor = True and Hot sichuan = True then 1.000
13 1 IF Chicken flavor = True and Cheese corn flavor = True then 1.000
10 1 IF Chicken flavor = True and Sauced beef flavor = True then 1.000
13 1 IF Cumin BBQ = True and Chives flavor = True then 1.000
12 1 IF Chives flavor = True and Hot sichuan = True then 1.000
14 0.929 IF Pork steak = True then 1.000
14 0.929 IF Chicken flavor = True then 1.000
14 0.929 IF Cumin BBQ = True then 1.000
13 0.923 IF Yolk = True then 1.000
13 0.923 IF Yolk = True and Chives flavor = True then 1.000
13 0.923 IF Cumin BBQ = True and Hot sichuan = True then 1.000
13 0.923 IF Cumin BBQ = True and Cheese corn flavor = True then 1.000
13 0.923 IF Chives flavor = True and Cheese corn flavor = True then 1.000
12 0.917 IF Yolk = True and Cheese corn flavor = True then 1.000
12 0.917 IF Chicken flavor = True and Kimchi flavor = True then 1.000
11 0.909 IF Cumin BBQ = True and Crab flavor = True then 1.000
11 0.909 IF Cumin BBQ = True and Sauced beef flavor = True then 1.000
11 0.909 IF Cumin BBQ = True and Kimchi flavor = True then 1.000
10 0.9 IF Yolk = True and Crab flavor = True then 1.000
10 0.9 IF Yolk = True and Sauced beef flavor = True then 1.000
10 0.9 IF Yolk = True and Kimchi flavor = True then 1.000
10 0.9 IF Tomato flavor = True and Hot sichuan = True then 1.000
Chives Flavor Rule Set
Chives Flavor = 1.000
ID Probability Rule
10 1 IF Chicken flavor = True and Sauced beef flavor = True then 1.000
11 1 IF Cumin BBQ = True and Crab flavor = True then 1.000
11 1 IF Cumin BBQ = True and Sauced beef flavor = True then 1.000
11 1 IF Cumin BBQ = True and Kimchi flavor = True then 1.000
12 1 IF Chicken flavor = True and Hot sichuan = True then 1.000
13 1 IF Chicken flavor = True and BBQ flavor = True then 1.000
13 1 IF Chicken flavor = True and Cheese corn flavor = True then 1.000
13 1 IF Cumin BBQ = True and Hot sichuan = True then 1.000
13 1 IF Cumin BBQ = True and Cheese corn flavor = True then 1.000
14 1 IF Pork steak = True then 1.000
14 1 IF Cumin BBQ = True then 1.000
13 1 IF Yolk = True then 1.000
4 1 IF Yolk = True and spices salt = True then 1.000
12 1 IF Yolk = True and Pork steak = True then 1.000
11 1 IF Yolk = True and Chicken flavor = True then 1.000
91
12 1 IF Yolk = True and Cumin BBQ = True then 1.000
10 1 IF Yolk = True and Crab flavor = True then 1.000
8 1 IF Yolk = True and Tomato flavor = True then 1.000
6 1 IF Yolk = True and Curry beef = True then 1.000
7 1 IF Yolk = True and Pepper beef steak = True then 1.000
11 1 IF Yolk = True and Hot sichuan = True then 1.000
12 1 IF Yolk = True and BBQ flavor = True then 1.000
12 1 IF Yolk = True and Cheese corn flavor = True then 1.000
10 1 IF Yolk = True and Sauced beef flavor = True then 1.000
10 1 IF Yolk = True and Kimchi flavor = True then 1.000
4 1 IF spices salt = True and Pork steak = True then 1.000
12 1 IF Pork steak = True and Chicken flavor = True then 1.000
13 1 IF Pork steak = True and Cumin BBQ = True then 1.000
10 1 IF Pork steak = True and Crab flavor = True then 1.000
8 1 IF Pork steak = True and Tomato flavor = True then 1.000
6 0.929 IF Pork steak = True and Curry beef = True then 1.000
7 0.929 IF Pork steak = True and Pepper beef steak = True then 1.000
12 0.923 IF Pork steak = True and Hot sichuan = True then 1.000
13 0.923 IF Pork steak = True and BBQ flavor = True then 1.000
12 0.923 IF Pork steak = True and Cheese corn flavor = True then 1.000
10 0.923 IF Pork steak = True and Sauced beef flavor = True then 1.000
10 0.917 IF Pork steak = True and Kimchi flavor = True then 1.000
12 0.909 IF Chicken flavor = True and Cumin BBQ = True then 1.000
9 0.909 IF Chicken flavor = True and Crab flavor = True then 1.000
13 0.909 IF Cumin BBQ = True and BBQ flavor = True then 1.000
10 0.9 IF Crab flavor = True and BBQ flavor = True then 1.000
Cumin BBQ Flavor Rule Set
Cumin BBQ Flavor = 1.000
ID Probability Rule
12 1 IF Yolk = True and Pork steak = True then 1.000
11 1 IF Yolk = True and Chicken flavor = True then 1.000
11 1 IF Yolk = True and Hot sichuan = True then 1.000
12 1 IF Yolk = True and BBQ flavor = True then 1.000
4 1 IF spices salt = True and Pork steak = True then 1.000
12 1 IF Pork steak = True and Chicken flavor = True then 1.000
10 1 IF Pork steak = True and Crab flavor = True then 1.000
8 1 IF Pork steak = True and Tomato flavor = True then 1.000
6 1 IF Pork steak = True and Curry beef = True then 1.000
7 1 IF Pork steak = True and Pepper beef steak = True then 1.000
13 1 IF Pork steak = True and Chives flavor = True then 1.000
12 1 IF Pork steak = True and Hot sichuan = True then 1.000
92
13 1 IF Pork steak = True and BBQ flavor = True then 1.000
12 1 IF Pork steak = True and Cheese corn flavor = True then 1.000
10 1 IF Pork steak = True and Sauced beef flavor = True then 1.000
10 1 IF Pork steak = True and Kimchi flavor = True then 1.000
9 1 IF Chicken flavor = True and Crab flavor = True then 1.000
12 1 IF Chicken flavor = True and Chives flavor = True then 1.000
10 1 IF Crab flavor = True and BBQ flavor = True then 1.000
12 1 IF Chives flavor = True and Hot sichuan = True then 1.000BQ
13 1 IF Chives flavor = True and BBQ flavor = True then 1.000
14 0.929 IF Pork steak = True then 1.000
13 0.923 IF Yolk = True then 1.000
13 0.923 IF Yolk = True and Chives flavor = True then 1.000
13 0.923 IF Chicken flavor = True and BBQ flavor = True then 1.000
13 0.923 IF Chicken flavor = True and Cheese corn flavor = True then 1.000
13 0.923 IF Chives flavor = True and Cheese corn flavor = True then 1.000
12 0.917 IF Yolk = True and Cheese corn flavor = True then 1.000
12 0.917 IF Chicken flavor = True and Hot sichuan = True then 1.000
11 0.909 IF Crab flavor = True and Hot sichuan = True then 1.000
10 0.9 IF Yolk = True and Crab flavor = True then 1.000
10 0.9 IF Yolk = True and Sauced beef flavor = True then 1.000
10 0.9 IF Yolk = True and Kimchi flavor = True then 1.000
10 0.9 IF Chicken flavor = True and Sauced beef flavor = True then 1.000
Pork Steak Flavor Rule Set
Pork Steak Flavor = 1.000
ID Probability Rule
11 1 IF Yolk = True and Chicken flavor = True then 1.000
12 1 IF Yolk = True and Cumin BBQ = True then 1.000
11 1 IF Yolk = True and Hot sichuan = True then 1.000
12 1 IF Yolk = True and BBQ flavor = True then 1.000
12 1 IF Chicken flavor = True and Cumin BBQ = True then 1.000
9 1 IF Chicken flavor = True and Crab flavor = True then 1.000
12 1 IF Chicken flavor = True and Chives flavor = True then 1.000
13 1 IF Cumin BBQ = True and Chives flavor = True then 1.000
13 1 IF Cumin BBQ = True and BBQ flavor = True then 1.000
10 1 IF Crab flavor = True and BBQ flavor = True then 1.000
12 1 IF Chives flavor = True and Hot sichuan = True then 1.000
13 1 IF Chives flavor = True and BBQ flavor = True then 1.000
14 0.929 IF Cumin BBQ = True then 1.000
13 0.923 IF Yolk = True then 1.000
13 0.923 IF Yolk = True and Chives flavor = True then 1.000
13 0.923 IF Chicken flavor = True and BBQ flavor = True then 1.000
93
13 0.923 IF Chicken flavor = True and Cheese corn flavor = True then 1.000
13 0.923 IF Cumin BBQ = True and Hot sichuan = True then 1.000
13 0.923 IF Cumin BBQ = True and Cheese corn flavor = True then 1.000
13 0.923 IF Chives flavor = True and Cheese corn flavor = True then 1.000
12 0.917 IF Yolk = True and Cheese corn flavor = True then 1.000
12 0.917 IF Chicken flavor = True and Hot sichuan = True then 1.000
11 0.909 IF Cumin BBQ = True and Crab flavor = True then 1.000
11 0.909 IF Cumin BBQ = True and Sauced beef flavor = True then 1.000
11 0.909 IF Cumin BBQ = True and Kimchi flavor = True then 1.000
10 0.9 IF Yolk = True and Crab flavor = True then 1.000
10 0.9 IF Yolk = True and Sauced beef flavor = True then 1.000
10 0.9 IF Yolk = True and Kimchi flavor = True then 1.000
10 0.9 IF Chicken flavor = True and Sauced beef flavor = True then 1.000
Sauced Beef Flavor Rule Set
Sauced Beef Flavor = 1.000
ID Probability Rule
4 1 IF Yolk = True and spices salt = True then 1.000
6 1 IF Yolk = True and Curry beef = True then 1.000
7 1 IF Yolk = True and Pepper beef steak = True then 1.000
4 1 IF spices salt = True and Pork steak = True then 1.000
5 1 IF spices salt = True and Cumin BBQ = True then 1.000
7 1 IF spices salt = True and Chives flavor = True then 1.000
7 1 IF spices salt = True and BBQ flavor = True then 1.000
9 1 IF spices salt = True and Cheese corn flavor = True then 1.000
6 1 IF Pork steak = True and Curry beef = True then 1.000
7 1 IF Pork steak = True and Pepper beef steak = True then 1.000
7 1 IF Cumin BBQ = True and Curry beef = True then 1.000
8 1 IF Cumin BBQ = True and Pepper beef steak = True then 1.000
9 1 IF Curry beef = True and Chives flavor = True then 1.000
9 1 IF Curry beef = True and Hot sichuan = True then 1.000
9 1 IF Curry beef = True and BBQ flavor = True then 1.000
11 1 IF Curry beef = True and Cheese corn flavor = True then 1.000
8 1 IF Pepper beef steak = True and Chives flavor = True then 1.000
10 1 IF Pepper beef steak = True and BBQ flavor = True then 1.000
12 1 IF Pepper beef steak = True and Cheese corn flavor = True then 1.000
12 0.917 IF Tomato flavor = True and Cheese corn flavor = True then 1.000
11 0.909 IF Crab flavor = True and Curry beef = True then 1.000
11 0.909 IF Crab flavor = True and Pepper beef steak = True then 1.000
11 0.909 IF Tomato flavor = True and BBQ flavor = True then 1.000
11 0.909 IF Pepper beef steak = True and Hot sichuan = True then 1.000
10 0.9 IF Tomato flavor = True and Chives flavor = True then 1.000
94
10 0.9 IF Tomato flavor = True and Hot sichuan = True then 1.000
Hot & Spice Sichuan Flavor Rule Set
Hot & Spice Sichuan Flavor = 1.000
ID Probability Rule
14 0.929 IF Cumin BBQ = True then 1.000
13 0.923 IF Pork steak = True and Cumin BBQ = True then 1.000
13 0.923 IF Pork steak = True and Chives flavor = True then 1.000
13 0.923 IF Pork steak = True and BBQ flavor = True then 1.000
13 0.923 IF Chicken flavor = True and BBQ flavor = True then 1.000
13 0.923 IF Chicken flavor = True and Cheese corn flavor = True then 1.000
13 0.923 IF Cumin BBQ = True and Chives flavor = True then 1.000
13 0.923 IF Cumin BBQ = True and BBQ flavor = True then 1.000
13 0.923 IF Cumin BBQ = True and Cheese corn flavor = True then 1.000
13 0.923 IF Chives flavor = True and BBQ flavor = True then 1.000
12 0.917 IF Yolk = True and Pork steak = True then 1.000
12 0.917 IF Yolk = True and Cumin BBQ = True then 1.000
12 0.917 IF Yolk = True and BBQ flavor = True then 1.000
12 0.917 IF Pork steak = True and Chicken flavor = True then 1.000
12 0.917 IF Pork steak = True and Cheese corn flavor = True then 1.000
12 0.917 IF Chicken flavor = True and Cumin BBQ = True then 1.000
12 0.917 IF Chicken flavor = True and Chives flavor = True then 1.000
11 0.909 IF Yolk = True and Chicken flavor = True then 1.000
11 0.909 IF Cumin BBQ = True and Crab flavor = True then 1.000
11 0.909 IF Cumin BBQ = True and Sauced beef flavor = True then 1.000
11 0.909 IF Cumin BBQ = True and Kimchi flavor = True then 1.000
10 0.9 IF Pork steak = True and Crab flavor = True then 1.000
10 0.9 IF Pork steak = True and Sauced beef flavor = True then 1.000
10 0.9 IF Pork steak = True and Kimchi flavor = True then 1.000
10 0.9 IF Chicken flavor = True and Sauced beef flavor = True then 1.000
10 0.9 IF Crab flavor = True and BBQ flavor = True then 1.000
Curry Beef Flavor Rule Set
Curry Beef Flavor = 1.000
ID Probability Rule
4 1 IF Yolk = True and spices salt = True then 1.000
4 1 IF spices salt = True and Pork steak = True then 1.000
6 1 IF spices salt = True and Chicken flavor = True then 1.000
5 1 IF spices salt = True and Cumin BBQ = True then 1.000
9 1 IF spices salt = True and Crab flavor = True then 1.000
7 1 IF spices salt = True and Chives flavor = True then 1.000
7 1 IF spices salt = True and BBQ flavor = True then 1.000
9 1 IF spices salt = True and Cheese corn flavor = True then 1.000
95
13 1 IF spices salt = True and Sauced beef flavor = True then 1.000
16 1 IF spices salt = True and Kimchi flavor = True then 1.000
17 0.941 IF Pepper beef steak = True and Kimchi flavor = True then 1.000
15 0.933 IF spices salt = True and Pepper beef steak = True then 1.000
14 0.929 IF Pepper beef steak = True and Sauced beef flavor = True then 1.000
13 0.923 IF spices salt = True and Tomato flavor = True then 1.000
13 0.923 IF Tomato flavor = True and Pepper beef steak = True then 1.000
12 0.917 IF Pepper beef steak = True and Cheese corn flavor = True then 1.000
11 0.909 IF Crab flavor = True and Pepper beef steak = True then 1.000
10 0.9 IF Pepper beef steak = True and BBQ flavor = True then 1.000
Pepper Beef Steak Flavor Rule Set
Pepper Beef Steak Flavor = 1.000
ID Probability Rule
4 1 IF Yolk = True and spices salt = True then 1.000
6 1 IF Yolk = True and Curry beef = True then 1.000
4 1 IF spices salt = True and Pork steak = True then 1.000
6 1 IF spices salt = True and Chicken flavor = True then 1.000
5 1 IF spices salt = True and Cumin BBQ = True then 1.000
8 1 IF spices salt = True and Hot sichuan = True then 1.000
7 1 IF spices salt = True and BBQ flavor = True then 1.000
9 1 IF spices salt = True and Cheese corn flavor = True then 1.000
6 1 IF Pork steak = True and Curry beef = True then 1.000
8 1 IF Chicken flavor = True and Curry beef = True then 1.000
7 1 IF Cumin BBQ = True and Curry beef = True then 1.000
9 1 IF Crab flavor = True and Tomato flavor = True then 1.000
9 1 IF Curry beef = True and Hot sichuan = True then 1.000
9 1 IF Curry beef = True and BBQ flavor = True then 1.000
11 1 IF Curry beef = True and Cheese corn flavor = True then 1.000
14 0.929 IF Tomato flavor = True and Kimchi flavor = True then 1.000
13 0.923 IF Tomato flavor = True and Curry beef = True then 1.000
11 0.909 IF Crab flavor = True and Curry beef = True then 1.000
Yolk Flavor Rule Set
Yolk Flavor = 1.000
ID Probability Rule
13 0.923 IF Pork steak = True and Cumin BBQ = True then 1.000
13 0.923 IF Pork steak = True and Chives flavor = True then 1.000
13 0.923 IF Pork steak = True and BBQ flavor = True then 1.000
13 0.923 IF Cumin BBQ = True and Chives flavor = True then 1.000
13 0.923 IF Cumin BBQ = True and BBQ flavor = True then 1.000
13 0.923 IF Chives flavor = True and BBQ flavor = True then 1.000
13 0.923 IF Chives flavor = True and Cheese corn flavor = True then 1.000
96
12 0.917 IF Pork steak = True and Chicken flavor = True then 1.000
12 0.917 IF Pork steak = True and Hot sichuan = True then 1.000
12 0.917 IF Pork steak = True and Cheese corn flavor = True then 1.000
12 0.917 IF Chicken flavor = True and Cumin BBQ = True then 1.000
12 0.917 IF Chicken flavor = True and Chives flavor = True then 1.000
12 0.917 IF Chives flavor = True and Hot sichuan = True then 1.000
10 0.9 IF Pork steak = True and Crab flavor = True then 1.000
10 0.9 IF Pork steak = True and Sauced beef flavor = True then 1.000
10 0.9 IF Pork steak = True and Kimchi flavor = True then 1.000
10 0.9 IF Crab flavor = True and BBQ flavor = True then 1.000
Crab Flavor Rule Set
Crab Flavor = 1.000
ID Probability Rule
4 1 IF Yolk = True and spices salt = True then 1.000
6 1 IF Yolk = True and Curry beef = True then 1.000
7 1 IF Yolk = True and Pepper beef steak = True then 1.000
4 1 IF spices salt = True and Pork steak = True then 1.000
5 1 IF spices salt = True and Cumin BBQ = True then 1.000
6 1 IF Pork steak = True and Curry beef = True then 1.000
7 1 IF Pork steak = True and Pepper beef steak = True then 1.000
7 1 IF Cumin BBQ = True and Curry beef = True then 1.000
8 1 IF Cumin BBQ = True and Pepper beef steak = True then 1.000
8 1 IF Pepper beef steak = True and Chives flavor = True then 1.000
Tomato Flavor Rule Set
Tomato Flavor = 1.000
ID Probability Rule
4 1 IF Yolk = True and spices salt = True then 1.000
4 1 IF spices salt = True and Pork steak = True then 1.000
5 1 IF spices salt = True and Cumin BBQ = True then 1.000
7 1 IF spices salt = True and BBQ flavor = True then 1.000
10 0.9 IF Pepper beef steak = True and BBQ flavor = True then 1.000
Hot & Spice Salt Flavor Rule Set
Hot & Spice Salt Flavor = 1.000
ID Probability Rule
4 0.923 IF Tomato flavor = True and Curry beef = True then 1.000
Chicken Flavor Rule Set
Chicken Flavor = 1.000
ID Probability Rule
10 1 IF Yolk = True and Kimchi flavor = True then 1.000
10 1 IF Pork steak = True and Crab flavor = True then 1.000
10 1 IF Pork steak = True and Sauced beef flavor = True then 1.000
97
10 1 IF Crab flavor = True and BBQ flavor = True then 1.000
11 1 IF Yolk = True and Hot sichuan = True then 1.000
11 1 IF Cumin BBQ = True and Kimchi flavor = True then 1.000lavor
12 0.929 IF Yolk = True and Pork steak = True then 1.000
12 0.923 IF Yolk = True and Cumin BBQ = True then 1.000
12 0.923 IF Yolk = True and BBQ flavor = True then 1.000
12 0.923 IF Yolk = True and Cheese corn flavor = True then 1.000
12 0.923 IF Pork steak = True and Hot sichuan = True then 1.000
12 0.923 IF Chives flavor = True and Hot sichuan = True then 1.000
13 0.923 IF Pork steak = True and Cumin BBQ = True then 1.000
13 0.923 IF Pork steak = True and Chives flavor = True then 1.000
13 0.923 IF Pork steak = True and BBQ flavor = True then 1.000
13 0.917 IF Cumin BBQ = True and Chives flavor = True then 1.000
13 0.917 IF Cumin BBQ = True and BBQ flavor = True then 1.000
13 0.917 IF Cumin BBQ = True and Cheese corn flavor = True then 1.000
13 0.917 IF Chives flavor = True and BBQ flavor = True then 1.000
13 0.917 IF Chives flavor = True and Cheese corn flavor = True then 1.000
14 0.917 IF BBQ flavor = True and Cheese corn flavor = True then 1.000
4 0.909 IF spices salt = True and Pork steak = True then 1.000
8 0.909 IF Pork steak = True and Tomato flavor = True then 1.000
6 0.9 IF Pork steak = True and Curry beef = True then 1.000
7 0.9 IF Pork steak = True and Pepper beef steak = True then Chicken Flavor
12 0.9 IF Pork steak = True and Cheese corn flavor = True then Chicken Flavor
10 0.9 IF Pork steak = True and Kimchi flavor = True then Chicken Flavor Table 6 Scoring information for Top 10 Rules in the North China Region Jan. May Sep. Feb. Jun. Nov. Mar
. Aug. Dec. May
TF 1 1 1 0 0 0 1 1 1 0 CF 1 0 1 0 0 1 0 0 1 0 SBF 0 0 1 0 1 1 0 1 1 0 CCF 0 0 1 0 1 0 1 1 1 0 BQF 0 0 1 0 1 0 1 1 0 0 PBS 1 0 1 0 0 0 0 1 1 0 CKF 0 0 1 0 1 0 1 0 0 0 CBF 1 0 1 0 0 1 0 1 1 0 CBQ 0 0 1 0 1 0 1 0 1 0 HSS 1 1 1 0 0 1 0 1 1 0 PSF 0 0 1 0 1 0 1 0 0 0 YF 0 0 1 0 1 0 1 0 0 0 KF 1 0 1 0 1 1 1 1 1 0 CVF 0 0 1 0 1 1 1 0 0 0
98
HSC 0 0 1 0 1 0 1 0 1 0 Scoring Information
Prediction 1 PBS CBF CVF CVF KF CVF KF PBS Confidence 1 1 0.92 1 1 1 1 1 1 Rule ID 1 94 234 4 4 58 4 5 94 Prediction 2 KF PBS CCF CBF CCF CBF KF Confidence 2 1 1 1 1 1 1 1 Rule ID 2 95 94 79 104 96 6 95 Prediction 3 CBF KF BQF SBF BQF SBF CCF Confidence 3 1 1 1 1 1 1 1 Rule ID 3 104 95 80 114 97 21 98 Table 7 Results for the South China Region
ID Consequent Antecedent Support % Confidence % Lift
1 YF PSF 30.556 100 2.769
2 CBQ PSF 30.556 100 2.769
3 CKF PSF 30.556 100 2.571
4 HSC PSF 30.556 100 2
5 CVF PSF 30.556 100 2.118
6 BQF PSF 30.556 100 2
7 CKF CBQ 36.111 100 2.571
8 CVF CBQ 36.111 100 2.118
9 BQF CBQ 36.111 100 2
10 YF PSF and CF 11.111 100 2.769
11 CBQ PSF and YF 30.556 100 2.769
12 YF PSF and CBQ 30.556 100 2.769
13 CKF PSF and YF 30.556 100 2.571
14 YF PSF and CKF 30.556 100 2.769
15 YF PSF and TF 16.667 100 2.769
16 HSC PSF and YF 30.556 100 2
17 YF PSF and HSC 30.556 100 2.769
18 PSF YF and HSC 30.556 100 3.273
19 CVF PSF and YF 30.556 100 2.118
20 YF PSF and CVF 30.556 100 2.769
21 BQF PSF and YF 30.556 100 2
22 YF PSF and BQF 30.556 100 2.769
23 YF PSF and SBF 27.778 100 2.769
24 YF PSF and CCF 25 100 2.769
25 YF PSF and KF 25 100 2.769
26 CBQ PSF and CF 11.111 100 2.769
27 CKF PSF and CF 11.111 100 2.571
99
28 HSC PSF and CF 11.111 100 2
29 CVF PSF and CF 11.111 100 2.118
30 BQF PSF and CF 11.111 100 2
31 CCF PSF and CF 11.111 100 1.895
32 KF PSF and CF 11.111 100 1.8
33 CKF PSF and CBQ 30.556 100 2.571
34 CBQ PSF and CKF 30.556 100 2.769
35 CBQ PSF and TF 16.667 100 2.769
36 HSC PSF and CBQ 30.556 100 2
37 CBQ PSF and HSC 30.556 100 2.769
38 CVF PSF and CBQ 30.556 100 2.118
39 CBQ PSF and CVF 30.556 100 2.769
40 BQF PSF and CBQ 30.556 100 2
41 CBQ PSF and BQF 30.556 100 2.769
42 CBQ PSF and SBF 27.778 100 2.769
43 CBQ PSF and CCF 25 100 2.769
44 CBQ PSF and KF 25 100 2.769
45 CKF PSF and TF 16.667 100 2.571
46 HSC PSF and CKF 30.556 100 2
47 CKF PSF and HSC 30.556 100 2.571
48 CVF PSF and CKF 30.556 100 2.118
49 CKF PSF and CVF 30.556 100 2.571
50 BQF PSF and CKF 30.556 100 2
51 CKF PSF and BQF 30.556 100 2.571
52 CKF PSF and SBF 27.778 100 2.571
53 CKF PSF and CCF 25 100 2.571
54 CKF PSF and KF 25 100 2.571
55 HSC PSF and TF 16.667 100 2
56 CVF PSF and TF 16.667 100 2.118
57 BQF PSF and TF 16.667 100 2
58 SBF PSF and TF 16.667 100 1.8
59 CCF PSF and TF 16.667 100 1.895
60 CVF PSF and HSC 30.556 100 2.118
61 HSC PSF and CVF 30.556 100 2
62 BQF PSF and HSC 30.556 100 2
63 HSC PSF and BQF 30.556 100 2
64 HSC PSF and SBF 27.778 100 2
65 HSC PSF and CCF 25 100 2
66 HSC PSF and KF 25 100 2
67 BQF PSF and CVF 30.556 100 2
68 CVF PSF and BQF 30.556 100 2.118
100
69 CVF PSF and SBF 27.778 100 2.118
70 CVF PSF and CCF 25 100 2.118
71 CVF PSF and KF 25 100 2.118
72 BQF PSF and SBF 27.778 100 2
73 BQF PSF and CCF 25 100 2
74 BQF PSF and KF 25 100 2
75 CBQ YF and CF 13.889 100 2.769
76 CKF YF and CF 13.889 100 2.571
77 CVF YF and CF 13.889 100 2.118
78 BQF YF and CF 13.889 100 2
79 CCF YF and CF 13.889 100 1.895
80 KF YF and CF 13.889 100 1.8
81 CKF YF and CBQ 33.333 100 2.571
82 CBQ YF and CKF 33.333 100 2.769
83 CBQ YF and TF 19.444 100 2.769
84 CBQ YF and HSC 30.556 100 2.769
85 CVF YF and CBQ 33.333 100 2.118
86 CBQ YF and CVF 33.333 100 2.769
87 BQF YF and CBQ 33.333 100 2
88 CBQ YF and BQF 33.333 100 2.769
89 CBQ YF and SBF 30.556 100 2.769
90 CBQ YF and CCF 27.778 100 2.769
91 CBQ YF and KF 27.778 100 2.769
92 CKF YF and TF 19.444 100 2.571
93 CKF YF and HSC 30.556 100 2.571
94 CVF YF and CKF 33.333 100 2.118
95 CKF YF and CVF 33.333 100 2.571
96 BQF YF and CKF 33.333 100 2
97 CKF YF and BQF 33.333 100 2.571
98 CKF YF and SBF 30.556 100 2.571
99 CKF YF and CCF 27.778 100 2.571
100 CKF YF and KF 27.778 100 2.571
101 CVF YF and TF 19.444 100 2.118
102 BQF YF and TF 19.444 100 2
103 SBF YF and TF 19.444 100 1.8
104 CCF YF and TF 19.444 100 1.895
105 CVF YF and HSC 30.556 100 2.118
106 BQF YF and HSC 30.556 100 2
107 BQF YF and CVF 33.333 100 2
108 CVF YF and BQF 33.333 100 2.118
109 CVF YF and SBF 30.556 100 2.118
101
110 CVF YF and CCF 27.778 100 2.118
111 CVF YF and KF 27.778 100 2.118
112 BQF YF and SBF 30.556 100 2
113 BQF YF and CCF 27.778 100 2
114 BQF YF and KF 27.778 100 2
115 HSS CBF and PBS 41.667 100 1.8
116 HSS CBF and CKF 11.111 100 1.8
117 CBF HSS and CKF 11.111 100 1.895
118 HSS CBF and HSC 22.222 100 1.8
119 CBF HSS and HSC 22.222 100 1.895
120 HSS CBF and CVF 19.444 100 1.8
121 CBF HSS and CVF 19.444 100 1.895
122 HSS CBF and BQF 22.222 100 1.8
123 CBF HSS and BQF 22.222 100 1.895
124 HSS CBF and CCF 30.556 100 1.8
125 CBF HSS and CCF 30.556 100 1.895
126 HSS CBF and KF 33.333 100 1.8
127 CBF HSS and KF 33.333 100 1.895
128 CF CBF and CKF 11.111 100 2.118
129 CF CBF and CVF 19.444 100 2.118
130 PBS CBF and CKF 11.111 100 2
131 PBS CBF and CVF 19.444 100 2
132 PBS CBF and BQF 22.222 100 2
133 PBS CBF and CCF 30.556 100 2
134 PBS CBF and KF 33.333 100 2
135 TF CBF and CKF 11.111 100 2
136 SBF CBF and CKF 11.111 100 1.8
137 CCF CBF and CKF 11.111 100 1.895
138 KF CBF and CKF 11.111 100 1.8
139 TF CBF and CVF 19.444 100 2
140 KF CBF and CVF 19.444 100 1.8
141 CCF CBF and BQF 22.222 100 1.895
142 KF CBF and BQF 22.222 100 1.8
143 KF CBF and CCF 30.556 100 1.8
144 CF HSS and CKF 11.111 100 2.118
145 CF HSS and CVF 19.444 100 2.118
146 PBS HSS and CKF 11.111 100 2
147 PBS HSS and TF 33.333 100 2
148 PBS HSS and CVF 19.444 100 2
149 PBS HSS and BQF 22.222 100 2
150 PBS HSS and CCF 30.556 100 2
102
151 PBS HSS and KF 33.333 100 2
152 TF HSS and CKF 11.111 100 2
153 SBF HSS and CKF 11.111 100 1.8
154 CCF HSS and CKF 11.111 100 1.895
155 KF HSS and CKF 11.111 100 1.8
156 TF HSS and CVF 19.444 100 2
157 KF HSS and CVF 19.444 100 1.8
158 CCF HSS and BQF 22.222 100 1.895
159 KF HSS and BQF 22.222 100 1.8
160 KF HSS and CCF 30.556 100 1.8
161 CF CBQ and PBS 11.111 100 2.118
162 CKF CF and CBQ 16.667 100 2.571
163 CVF CF and CBQ 16.667 100 2.118
164 BQF CF and CBQ 16.667 100 2
165 CCF CF and CBQ 16.667 100 1.895
166 KF CF and CBQ 16.667 100 1.8
167 CF PBS and CKF 13.889 100 2.118
168 CF PBS and CVF 22.222 100 2.118
169 CCF CF and CKF 19.444 100 1.895
170 KF CF and CKF 19.444 100 1.8
171 CCF CF and HSC 19.444 100 1.895
172 KF CF and HSC 19.444 100 1.8
173 KF CF and CVF 27.778 100 1.8
174 CCF CF and BQF 25 100 1.895
175 KF CF and BQF 25 100 1.8
176 KF CF and CCF 30.556 100 1.8
177 CKF CBQ and PBS 11.111 100 2.571
178 TF CBQ and PBS 11.111 100 2
179 CVF CBQ and PBS 11.111 100 2.118
180 BQF CBQ and PBS 11.111 100 2
181 SBF CBQ and PBS 11.111 100 1.8
182 CCF CBQ and PBS 11.111 100 1.895
183 KF CBQ and PBS 11.111 100 1.8
184 CKF CBQ and TF 22.222 100 2.571
185 CKF CBQ and HSC 33.333 100 2.571
186 CVF CBQ and CKF 36.111 100 2.118
187 CKF CBQ and CVF 36.111 100 2.571
188 CBQ CKF and CVF 36.111 100 2.769
189 BQF CBQ and CKF 36.111 100 2
190 CKF CBQ and BQF 36.111 100 2.571
191 CBQ CKF and BQF 36.111 100 2.769
103
192 CKF CBQ and SBF 33.333 100 2.571
193 CKF CBQ and CCF 30.556 100 2.571
194 CKF CBQ and KF 30.556 100 2.571
195 CVF CBQ and TF 22.222 100 2.118
196 BQF CBQ and TF 22.222 100 2
197 SBF CBQ and TF 22.222 100 1.8
198 CCF CBQ and TF 22.222 100 1.895
199 CVF CBQ and HSC 33.333 100 2.118
200 BQF CBQ and HSC 33.333 100 2
201 BQF CBQ and CVF 36.111 100 2
202 CVF CBQ and BQF 36.111 100 2.118
203 CVF CBQ and SBF 33.333 100 2.118
204 CVF CBQ and CCF 30.556 100 2.118
205 CVF CBQ and KF 30.556 100 2.118
206 BQF CBQ and SBF 33.333 100 2
207 BQF CBQ and CCF 30.556 100 2
208 BQF CBQ and KF 30.556 100 2
209 TF PBS and CKF 13.889 100 2
210 SBF PBS and CKF 13.889 100 1.8
211 CCF PBS and CKF 13.889 100 1.895
212 KF PBS and CKF 13.889 100 1.8
213 TF PBS and CVF 22.222 100 2
214 TF PBS and SBF 27.778 100 2
215 KF PBS and CVF 22.222 100 1.8
216 CCF PBS and BQF 25 100 1.895
217 KF PBS and BQF 25 100 1.8
218 KF PBS and CCF 33.333 100 1.8
219 SBF CKF and TF 25 100 1.8
220 CCF CKF and TF 25 100 1.895
221 BQF CKF and CVF 36.111 100 2
222 CVF CKF and BQF 36.111 100 2.118
223 CCF TF and HSC 30.556 100 1.895
224 CCF TF and BQF 33.333 100 1.895
225 BQF HSC and CVF 36.111 100 2
226 BQF CVF and SBF 38.889 100 2
227 KF CCF 52.778 94.737 1.705
228 HSS PBS 50 94.444 1.7
229 KF BQF and CCF 44.444 93.75 1.688
230 CCF BQF and KF 44.444 93.75 1.776
231 KF TF and CCF 41.667 93.333 1.68
232 CCF TF and KF 41.667 93.333 1.768
104
233 SBF CVF and BQF 41.667 93.333 1.68
234 CVF BQF and SBF 41.667 93.333 1.976
235 KF SBF and CCF 41.667 93.333 1.68
236 CCF SBF and KF 41.667 93.333 1.768
237 CBQ CKF 38.889 92.857 2.571
238 HSC CKF 38.889 92.857 1.857
239 CVF CKF 38.889 92.857 1.966
240 BQF CKF 38.889 92.857 1.857
241 SBF CKF 38.889 92.857 1.671
242 CCF TF and SBF 38.889 92.857 1.759
243 CVF HSC and BQF 38.889 92.857 1.966
244 KF HSC and CCF 38.889 92.857 1.671
245 CCF HSC and KF 38.889 92.857 1.759
246 BQF CVF and CCF 38.889 92.857 1.857
247 KF CVF and CCF 38.889 92.857 1.671
248 CBQ YF 36.111 92.308 2.556
249 YF CBQ 36.111 92.308 2.556
250 CKF YF 36.111 92.308 2.374
251 CVF YF 36.111 92.308 1.955
252 BQF YF 36.111 92.308 1.846
253 HSC CBQ 36.111 92.308 1.846
254 SBF CBQ 36.111 92.308 1.662
255 YF CBQ and CKF 36.111 92.308 2.556
256 YF CBQ and CVF 36.111 92.308 2.556
257 YF CBQ and BQF 36.111 92.308 2.556
258 YF CKF and CVF 36.111 92.308 2.556
259 YF CKF and BQF 36.111 92.308 2.556
260 CBF PBS and KF 36.111 92.308 1.749
261 HSS PBS and TF 36.111 92.308 1.662
262 HSS PBS and KF 36.111 92.308 1.662
263 HSC CBQ and CKF 36.111 92.308 1.846
264 CBQ CKF and HSC 36.111 92.308 2.556
265 SBF CBQ and CKF 36.111 92.308 1.662
266 CBQ CKF and SBF 36.111 92.308 2.556
267 HSC CBQ and CVF 36.111 92.308 1.846
268 CBQ HSC and CVF 36.111 92.308 2.556
269 HSC CBQ and BQF 36.111 92.308 1.846
270 SBF CBQ and CVF 36.111 92.308 1.662
271 SBF CBQ and BQF 36.111 92.308 1.662
272 KF PBS and TF 36.111 92.308 1.662
273 TF PBS and KF 36.111 92.308 1.846
105
274 CCF PBS and KF 36.111 92.308 1.749
275 CVF CKF and HSC 36.111 92.308 1.955
276 HSC CKF and CVF 36.111 92.308 1.846
277 CKF HSC and CVF 36.111 92.308 2.374
278 BQF CKF and HSC 36.111 92.308 1.846
279 HSC CKF and BQF 36.111 92.308 1.846
280 SBF CKF and HSC 36.111 92.308 1.662
281 HSC CKF and SBF 36.111 92.308 1.846
282 SBF CKF and CVF 36.111 92.308 1.662
283 CVF CKF and SBF 36.111 92.308 1.955
284 SBF CKF and BQF 36.111 92.308 1.662
285 BQF CKF and SBF 36.111 92.308 1.846
286 SBF HSC and CVF 36.111 92.308 1.662
287 PSF YF and CBQ 33.333 91.667 3
288 PSF YF and CKF 33.333 91.667 3
289 PSF YF and CVF 33.333 91.667 3
290 PSF YF and BQF 33.333 91.667 3
291 PSF CBQ and HSC 33.333 91.667 3
292 HSC YF and CBQ 33.333 91.667 1.833
293 YF CBQ and HSC 33.333 91.667 2.538
294 SBF YF and CBQ 33.333 91.667 1.65
295 YF CBQ and SBF 33.333 91.667 2.538
296 HSC YF and CKF 33.333 91.667 1.833
297 SBF YF and CKF 33.333 91.667 1.65
298 HSC YF and CVF 33.333 91.667 1.833
299 HSC YF and BQF 33.333 91.667 1.833
300 SBF YF and CVF 33.333 91.667 1.65
301 SBF YF and BQF 33.333 91.667 1.65
302 HSS CBF and TF 33.333 91.667 1.65
303 CBF HSS and TF 33.333 91.667 1.737
304 PBS CBF and TF 33.333 91.667 1.833
305 CBF PBS and CCF 33.333 91.667 1.737
306 KF CBF and TF 33.333 91.667 1.65
307 TF CBF and KF 33.333 91.667 1.833
308 CCF CBF and KF 33.333 91.667 1.737
309 PBS HSS and CF 33.333 91.667 1.833
310 HSS CF and PBS 33.333 91.667 1.65
311 HSS PBS and CCF 33.333 91.667 1.65
312 KF HSS and TF 33.333 91.667 1.65
313 TF HSS and KF 33.333 91.667 1.833
314 CCF HSS and KF 33.333 91.667 1.737
106
315 TF CF and PBS 33.333 91.667 1.833
316 PBS CF and TF 33.333 91.667 1.833
317 CCF CF and KF 33.333 91.667 1.737
318 CBQ CKF and CCF 33.333 91.667 2.538
319 CBQ CKF and KF 33.333 91.667 2.538
320 SBF CBQ and HSC 33.333 91.667 1.65
321 HSC CBQ and SBF 33.333 91.667 1.833
322 TF PBS and CCF 33.333 91.667 1.833
323 HSC CKF and CCF 33.333 91.667 1.833
324 HSC CKF and KF 33.333 91.667 1.833
325 CVF CKF and CCF 33.333 91.667 1.941
326 CVF CKF and KF 33.333 91.667 1.941
327 BQF CKF and CCF 33.333 91.667 1.833
328 BQF CKF and KF 33.333 91.667 1.833
329 SBF CKF and CCF 33.333 91.667 1.65
330 SBF CKF and KF 33.333 91.667 1.65
331 KF CKF and CCF 33.333 91.667 1.65
332 CCF CKF and KF 33.333 91.667 1.737
333 CCF TF and CVF 33.333 91.667 1.737
334 KF TF and CVF 33.333 91.667 1.65
335 SBF TF and BQF 33.333 91.667 1.65
336 KF TF and BQF 33.333 91.667 1.65
337 SBF PSF 30.556 90.909 1.636
338 SBF PSF and YF 30.556 90.909 1.636
339 PSF YF and SBF 30.556 90.909 2.975
340 SBF PSF and CBQ 30.556 90.909 1.636
341 SBF PSF and CKF 30.556 90.909 1.636
342 SBF PSF and HSC 30.556 90.909 1.636
343 SBF PSF and CVF 30.556 90.909 1.636
344 SBF PSF and BQF 30.556 90.909 1.636
345 YF CBQ and CCF 30.556 90.909 2.517
346 YF CBQ and KF 30.556 90.909 2.517
347 SBF YF and HSC 30.556 90.909 1.636
348 HSC YF and SBF 30.556 90.909 1.818
349 HSS CBF and CF 30.556 90.909 1.636
350 PBS CBF and CF 30.556 90.909 1.818
351 TF CBF and CF 30.556 90.909 1.818
352 TF CBF and CCF 30.556 90.909 1.818
353 TF HSS and CCF 30.556 90.909 1.818
354 HSC CBQ and CCF 30.556 90.909 1.818
355 HSC CBQ and KF 30.556 90.909 1.818
107
356 SBF CBQ and CCF 30.556 90.909 1.636
357 SBF CBQ and KF 30.556 90.909 1.636
358 KF CBQ and CCF 30.556 90.909 1.636
359 CCF CBQ and KF 30.556 90.909 1.722
360 SBF TF and HSC 30.556 90.909 1.636
361 KF TF and HSC 30.556 90.909 1.636
362 CCF KF 55.556 90 1.705
363 PSF YF and CCF 27.778 90 2.945
364 PSF YF and KF 27.778 90 2.945
365 HSC YF and CCF 27.778 90 1.8
366 HSC YF and KF 27.778 90 1.8
367 SBF YF and CCF 27.778 90 1.62
368 SBF YF and KF 27.778 90 1.62
369 KF YF and CCF 27.778 90 1.62
370 CCF YF and KF 27.778 90 1.705
371 HSS CBF and SBF 27.778 90 1.62
372 CBF HSS and SBF 27.778 90 1.705
373 PBS HSS and SBF 27.778 90 1.8
374 HSS PBS and SBF 27.778 90 1.62
375 TF HSS and SBF 27.778 90 1.8
376 PBS CF and SBF 27.778 90 1.8
377 CF PBS and SBF 27.778 90 1.906
378 TF CF and SBF 27.778 90 1.8
379 CCF CF and CVF 27.778 90 1.705
380 CCF CF and SBF 27.778 90 1.705
381 KF CF and SBF 27.778 90 1.62
382 CCF PBS and SBF 27.778 90 1.705
383 KF PBS and SBF 27.778 90 1.62 Table 8 Scoring for All Rule Sets (South China Region)
Hot & Spice Sichuan Flavor Rule Set
1.000 = Hot & Spice Sichuan Flavor
ID Probability Rule
11 1 if Pork steak = True then 1.000
11 1 if Pork steak = True and Yolk = True then 1.000
4 1 if Pork steak = True and Crab flavor = True then 1.000
11 1 if Pork steak = True and Cumin BBQ = True then 1.000
11 1 if Pork steak = True and Chicken flavor = True then 1.000
6 1 if Pork steak = True and Tomato flavor = True then 1.000
11 1 if Pork steak = True and Chives flavor = True then 1.000
11 1 if Pork steak = True and BBQ flavor = True then 1.000
108
10 1 if Pork steak = True and Sauced beef flavor = True then 1.000
9 1 if Pork steak = True and Cheese corn flavor = True then 1.000
9 1 if Pork steak = True and Kimchi flavor = True then 1.000
14 0.929 if Chicken flavor = True then 1.000
13 0.923 if Cumin BBQ = True then 1.000
13 0.923 if Cumin BBQ = True and Chicken flavor = True then 1.000
13 0.923 if Cumin BBQ = True and Chives flavor = True then 1.000
13 0.923 if Cumin BBQ = True and BBQ flavor = True then 1.000
13 0.923 if Chicken flavor = True and Chives flavor = True then 1.000
13 0.923 if Chicken flavor = True and BBQ flavor = True then 1.000
13 0.923 if Chicken flavor = True and Sauced beef flavor = True then 1.000
12 0.917 if Yolk = True and Cumin BBQ = True then 1.000
12 0.917 if Yolk = True and Chicken flavor = True then 1.000
12 0.917 if Yolk = True and Chives flavor = True then 1.000
12 0.917 if Yolk = True and BBQ flavor = True then 1.000
12 0.917 if Cumin BBQ = True and Sauced beef flavor = True then 1.000
12 0.917 if Chicken flavor = True and Cheese corn flavor = True then 1.000
12 0.917 if Chicken flavor = True and Kimchi flavor = True then 1.000
11 0.909 if Yolk = True and Sauced beef flavor = True then 1.000
11 0.909 if Cumin BBQ = True and Cheese corn flavor = True then 1.000
11 0.909 if Cumin BBQ = True and Kimchi flavor = True then 1.000
10 0.9 if Yolk = True and Cheese corn flavor = True then 1.000
10 0.9 if Yolk = True and Kimchi flavor = True then 1.000
Chives Flavor Rule Set
1.000 = Chives Flavor
ID Probability Rule
11 1 if Pork steak = True then 1.000
13 1 if Cumin BBQ = True then 1.000
11 1 if Pork steak = True and Yolk = True then 1.000
4 1 if Pork steak = True and Crab flavor = True then 1.000
11 1 if Pork steak = True and Cumin BBQ = True then 1.000
11 1 if Pork steak = True and Chicken flavor = True then 1.000
6 1 if Pork steak = True and Tomato flavor = True then 1.000
11 1 if Pork steak = True and Hot sichuan = True then 1.000
11 1 if Pork steak = True and BBQ flavor = True then 1.000
10 1 if Pork steak = True and Sauced beef flavor = True then 1.000
9 1 if Pork steak = True and Cheese corn flavor = True then 1.000
9 1 if Pork steak = True and Kimchi flavor = True then 1.000
5 1 if Yolk = True and Crab flavor = True then 1.000
12 1 if Yolk = True and Cumin BBQ = True then 1.000
12 1 if Yolk = True and Chicken flavor = True then 1.000
109
7 1 if Yolk = True and Tomato flavor = True then 1.000
11 1 if Yolk = True and Hot sichuan = True then 1.000
12 1 if Yolk = True and BBQ flavor = True then 1.000
11 1 if Yolk = True and Sauced beef flavor = True then 1.000
10 1 if Yolk = True and Cheese corn flavor = True then 1.000
10 1 if Yolk = True and Kimchi flavor = True then 1.000
6 1 if Crab flavor = True and Cumin BBQ = True then 1.000
4 1 if Cumin BBQ = True and Pepper beef steak = True then 1.000
13 1 if Cumin BBQ = True and Chicken flavor = True then 1.000
8 1 if Cumin BBQ = True and Tomato flavor = True then 1.000
12 1 if Cumin BBQ = True and Hot sichuan = True then 1.000
13 1 if Cumin BBQ = True and BBQ flavor = True then 1.000
12 1 if Cumin BBQ = True and Sauced beef flavor = True then 1.000
11 1 if Cumin BBQ = True and Cheese corn flavor = True then 1.000
11 1 if Cumin BBQ = True and Kimchi flavor = True then 1.000
13 1 if Chicken flavor = True and BBQ flavor = True then 1.000
15 0.933 if BBQ flavor = True and Sauced beef flavor = True then 1.000
14 0.929 if Chicken flavor = True then 1.000
14 0.929 if Hot sichuan = True and BBQ flavor = True then 1.000
13 0.923 if Yolk = True then 1.000
13 0.923 if Chicken flavor = True and Hot sichuan = True then 1.000
13 0.923 if Chicken flavor = True and Sauced beef flavor = True then 1.000
12 0.917 if Chicken flavor = True and Cheese corn flavor = True then 1.000
12 0.917 if Chicken flavor = True and Kimchi flavor = True then 1.000
Kimchi Flavor Rule Set
1.000 = Kimchi Flavor
ID Probability Rule
10 1 if Yolk = 1 and Cheese corn flavor = 1 then 1.000
10 1 if Crab flavor = 1 and Sauced beef flavor = 1 then 1.000
10 1 if Pepper beef steak = 1 and Sauced beef flavor = 1 then 1.000
11 1 if Cumin BBQ = 1 and Cheese corn flavor = 1 then 1.000
11 1 if Tomato flavor = 1 and Hot sichuan = 1 then 1.000
12 1 if Curry beef = 1 and Tomato flavor = 1 then 1.000
12 1 if spices salt = 1 and Tomato flavor = 1 then 1.000
12 1 if Chicken flavor = 1 and Cheese corn flavor = 1 then 1.000
12 1 if Tomato flavor = 1 and Chives flavor = 1 then 1.000
12 1 if Tomato flavor = 1 and BBQ flavor = 1 then 1.000
13 1 if Pepper beef steak = 1 and Tomato flavor = 1 then 1.000
14 1 if Hot sichuan = 1 and Cheese corn flavor = 1 then 1.000
14 1 if Chives flavor = 1 and Cheese corn flavor = 1 then 1.000
15 1 if Tomato flavor = 1 and Cheese corn flavor = 1 then 1.000
110
15 1 if Sauced beef flavor = 1 and Cheese corn flavor = 1 then 1.000
16 1 if BBQ flavor = 1 and Cheese corn flavor = 1 then 1.000
19 1 if Cheese corn flavor = 1 then 1.000
4 1 if Pork steak = 1 and Crab flavor = 1 then 1.000
5 1 if Yolk = 1 and Crab flavor = 1 then 1.000
4 1 if Curry beef = 1 and Chicken flavor = 1 then 1.000
7 1 if Curry beef = 1 and Chives flavor = 1 then 1.000
8 0.947 if Curry beef = 1 and BBQ flavor = 1 then 1.000
11 0.938 if Curry beef = 1 and Cheese corn flavor = 1 then 1.000
4 0.933 if spices salt = 1 and Chicken flavor = 1 then 1.000
7 0.933 if spices salt = 1 and Chives flavor = 1 then 1.000
8 0.929 if spices salt = 1 and BBQ flavor = 1 then 1.000
11 0.929 if spices salt = 1 and Cheese corn flavor = 1 then 1.000
6 0.923 if Crab flavor = 1 and Cumin BBQ = 1 then 1.000
7 0.917 if Crab flavor = 1 and Chicken flavor = 1 then 1.000
7 0.917 if Crab flavor = 1 and Hot sichuan = 1 then 1.000
10 0.917 if Crab flavor = 1 and Chives flavor = 1 then 1.000
9 0.917 if Crab flavor = 1 and BBQ flavor = 1 then 1.000
11 0.917 if Crab flavor = 1 and Cheese corn flavor = 1 then 1.000
4 0.909 if Cumin BBQ = 1 and Pepper beef steak = 1 then 1.000
5 0.909 if Pepper beef steak = 1 and Chicken flavor = 1 then 1.000
8 0.9 if Pepper beef steak = 1 and Chives flavor = 1 then 1.000
9 0.9 if Pepper beef steak = 1 and BBQ flavor = 1 then 1.000
12 0.9 if Pepper beef steak = 1 and Cheese corn flavor = 1 then 1.000
Yolk Flavor Rule Set
1.000 = Yolk Flavor
ID Probability Rule
11 1 if Pork steak = 1 then 1.000
4 1 if Pork steak = 1 and Crab flavor = 1 then 1.000
11 1 if Pork steak = 1 and Cumin BBQ = 1 then 1.000
11 1 if Pork steak = 1 and Chicken flavor = 1 then 1.000
6 1 if Pork steak = 1 and Tomato flavor = 1 then 1.000
11 1 if Pork steak = 1 and Hot sichuan = 1 then 1.000
11 1 if Pork steak = 1 and Chives flavor = 1 then 1.000
11 1 if Pork steak = 1 and BBQ flavor = 1 then 1.000
10 1 if Pork steak = 1 and Sauced beef flavor = 1 then 1.000
9 1 if Pork steak = 1 and Cheese corn flavor = 1 then 1.000
9 1 if Pork steak = 1 and Kimchi flavor = 1 then 1.000
13 0.923 if Cumin BBQ = 1 then 1.000
13 0.923 if Cumin BBQ = 1 and Chicken flavor = 1 then 1.000
13 0.923 if Cumin BBQ = 1 and Chives flavor = 1 then 1.000
111
13 0.923 if Cumin BBQ = 1 and BBQ flavor = 1 then 1.000
13 0.923 if Chicken flavor = 1 and Chives flavor = 1 then 1.000
13 0.923 if Chicken flavor = 1 and BBQ flavor = 1 then 1.000
12 0.917 if Cumin BBQ = 1 and Hot sichuan = 1 then 1.000
12 0.917 if Cumin BBQ = 1 and Sauced beef flavor = 1 then 1.000
11 0.909 if Cumin BBQ = 1 and Cheese corn flavor = 1 then 1.000
11 0.909 if Cumin BBQ = 1 and Kimchi flavor = 1 then 1.000
Pork Steak Flavor Rule Set
1.000 = Pork Steak Flavor
ID Probability Rule
11 1 if Yolk = 1 and Hot sichuan = 1 then 1.000
12 0.917 if Yolk = 1 and Cumin BBQ = 1 then 1.000
12 0.917 if Yolk = 1 and Chicken flavor = 1 then 1.000
12 0.917 if Yolk = 1 and Chives flavor = 1 then 1.000
12 0.917 if Yolk = 1 and BBQ flavor = 1 then 1.000
12 0.917 if Cumin BBQ = 1 and Hot sichuan = 1 then 1.000
11 0.909 if Yolk = 1 and Sauced beef flavor = 1 then 1.000
10 0.9 if Yolk = 1 and Cheese corn flavor = 1 then 1.000
10 0.9 if Yolk = 1 and Kimchi flavor = 1 then 1.000
Hot & Spice Salt Flavor Rule Set
1.000 = Hot & Spice Salt Flavor
ID Probability Rule
15 1 if Curry beef = 1 and Pepper beef steak = 1 then 1.000
4 1 if Curry beef = 1 and Chicken flavor = 1 then 1.000
8 1 if Curry beef = 1 and Hot sichuan = 1 then 1.000
7 1 if Curry beef = 1 and Chives flavor = 1 then 1.000
8 1 if Curry beef = 1 and BBQ flavor = 1 then 1.000
11 1 if Curry beef = 1 and Cheese corn flavor = 1 then 1.000
12 1 if Curry beef = 1 and Kimchi flavor = 1 then 1.000
18 0.944 if Pepper beef steak = 1 then 1.000
13 0.923 if Pepper beef steak = 1 and Tomato flavor = 1 then 1.000
13 0.923 if Pepper beef steak = 1 and Kimchi flavor = 1 then 1.000
12 0.917 if Curry beef = 1 and Tomato flavor = 1 then 1.000
12 0.917 if Crab flavor = 1 and Pepper beef steak = 1 then 1.000
12 0.917 if Pepper beef steak = 1 and Cheese corn flavor = 1 then 1.000
11 0.909 if Curry beef = 1 and Crab flavor = 1 then 1.000
10 0.9 if Curry beef = 1 and Sauced beef flavor = 1 then 1.000
10 0.9 if Pepper beef steak = 1 and Sauced beef flavor = 1 then 1.000
Cumin BBQ Flavor Rule Set
1.000 = Cumin BBQ Flavor
ID Probability Rule
112
11 1 if Pork steak = 1 then 1.000
11 1 if Pork steak = 1 and Yolk = 1 then 1.000
4 1 if Pork steak = 1 and Crab flavor = 1 then 1.000
11 1 if Pork steak = 1 and Chicken flavor = 1 then 1.000
6 1 if Pork steak = 1 and Tomato flavor = 1 then 1.000
11 1 if Pork steak = 1 and Hot sichuan = 1 then 1.000
11 1 if Pork steak = 1 and Chives flavor = 1 then 1.000
11 1 if Pork steak = 1 and BBQ flavor = 1 then 1.000
10 1 if Pork steak = 1 and Sauced beef flavor = 1 then 1.000
9 1 if Pork steak = 1 and Cheese corn flavor = 1 then 1.000
9 1 if Pork steak = 1 and Kimchi flavor = 1 then 1.000
5 1 if Yolk = 1 and Crab flavor = 1 then 1.000
12 1 if Yolk = 1 and Chicken flavor = 1 then 1.000
7 1 if Yolk = 1 and Tomato flavor = 1 then 1.000
11 1 if Yolk = 1 and Hot sichuan = 1 then 1.000
12 1 if Yolk = 1 and Chives flavor = 1 then 1.000
12 1 if Yolk = 1 and BBQ flavor = 1 then 1.000
11 1 if Yolk = 1 and Sauced beef flavor = 1 then 1.000
10 1 if Yolk = 1 and Cheese corn flavor = 1 then 1.000
10 1 if Yolk = 1 and Kimchi flavor = 1 then 1.000
13 1 if Chicken flavor = 1 and Chives flavor = 1 then 1.000
13 1 if Chicken flavor = 1 and BBQ flavor = 1 then 1.000
14 0.929 if Chicken flavor = 1 then 1.000
13 0.923 if Yolk = 1 then 1.000
13 0.923 if Chicken flavor = 1 and Hot sichuan = 1 then 1.000
13 0.923 if Chicken flavor = 1 and Sauced beef flavor = 1 then 1.000
13 0.923 if Hot sichuan = 1 and Chives flavor = 1 then 1.000
12 0.917 if Chicken flavor = 1 and Cheese corn flavor = 1 then 1.000
12 0.917 if Chicken flavor = 1 and Kimchi flavor = 1 then 1.000
Curry Beef Flavor Rule Set
1.000 = Curry Beef Flavor
ID Probability Rule
4 1 if spices salt = 1 and Chicken flavor = 1 then 1.000
8 1 if spices salt = 1 and Hot sichuan = 1 then 1.000
7 1 if spices salt = 1 and Chives flavor = 1 then 1.000
8 1 if spices salt = 1 and BBQ flavor = 1 then 1.000
11 1 if spices salt = 1 and Cheese corn flavor = 1 then 1.000
12 1 if spices salt = 1 and Kimchi flavor = 1 then 1.000
13 0.923 if Pepper beef steak = 1 and Kimchi flavor = 1 then 1.000
12 0.917 if spices salt = 1 and Tomato flavor = 1 then 1.000
12 0.917 if Pepper beef steak = 1 and Cheese corn flavor = 1 then 1.000
113
10 0.9 if spices salt = 1 and Sauced beef flavor = 1 then 1.000
Chicken Flavor Rule Set
1.000 = Chicken Flavor
ID Probability Rule
11 1 if Pork steak = 1 then 1.000
13 1 if Cumin BBQ = 1 then 1.000
11 1 if Pork steak = 1 and Yolk = 1 then 1.000
4 1 if Pork steak = 1 and Crab flavor = 1 then 1.000
11 1 if Pork steak = 1 and Cumin BBQ = 1 then 1.000
6 1 if Pork steak = 1 and Tomato flavor = 1 then 1.000
11 1 if Pork steak = 1 and Hot sichuan = 1 then 1.000
11 1 if Pork steak = 1 and Chives flavor = 1 then 1.000
11 1 if Pork steak = 1 and BBQ flavor = 1 then 1.000
10 1 if Pork steak = 1 and Sauced beef flavor = 1 then 1.000
9 1 if Pork steak = 1 and Cheese corn flavor = 1 then 1.000
9 1 if Pork steak = 1 and Kimchi flavor = 1 then 1.000
5 1 if Yolk = 1 and Crab flavor = 1 then 1.000
12 1 if Yolk = 1 and Cumin BBQ = 1 then 1.000
7 1 if Yolk = 1 and Tomato flavor = 1 then 1.000
11 1 if Yolk = 1 and Hot sichuan = 1 then 1.000
12 1 if Yolk = 1 and Chives flavor = 1 then 1.000
12 1 if Yolk = 1 and BBQ flavor = 1 then 1.000
11 1 if Yolk = 1 and Sauced beef flavor = 1 then 1.000
10 1 if Yolk = 1 and Cheese corn flavor = 1 then 1.000
10 1 if Yolk = 1 and Kimchi flavor = 1 then 1.000
6 1 if Crab flavor = 1 and Cumin BBQ = 1 then 1.000
4 1 if Cumin BBQ = 1 and Pepper beef steak = 1 then 1.000
8 1 if Cumin BBQ = 1 and Tomato flavor = 1 then 1.000
12 1 if Cumin BBQ = 1 and Hot sichuan = 1 then 1.000
13 1 if Cumin BBQ = 1 and Chives flavor = 1 then 1.000
13 1 if Cumin BBQ = 1 and BBQ flavor = 1 then 1.000
12 1 if Cumin BBQ = 1 and Sauced beef flavor = 1 then 1.000
11 1 if Cumin BBQ = 1 and Cheese corn flavor = 1 then 1.000
11 1 if Cumin BBQ = 1 and Kimchi flavor = 1 then 1.000
13 0.923 if Yolk = 1 then 1.000
13 0.923 if Hot sichuan = 1 and Chives flavor = 1 then 1.000
Pepper Beef Steak Flavor Rule Set
1.000 = Pepper Beef Steak Flavor
ID Probability Rule
8 1 if Curry beef = 1 and BBQ flavor = 1 then 1.000
11 1 if Curry beef = 1 and Cheese corn flavor = 1 then 1.000
114
12 1 if Curry beef = 1 and Kimchi flavor = 1 then 1.000
4 1 if spices salt = 1 and Chicken flavor = 1 then 1.000
12 1 if spices salt = 1 and Tomato flavor = 1 then 1.000
7 1 if spices salt = 1 and Chives flavor = 1 then 1.000
8 1 if spices salt = 1 and BBQ flavor = 1 then 1.000
11 1 if spices salt = 1 and Cheese corn flavor = 1 then 1.000
12 1 if spices salt = 1 and Kimchi flavor = 1 then 1.000
12 0.917 if Curry beef = 1 and Tomato flavor = 1 then 1.000
12 0.917 if spices salt = 1 and Crab flavor = 1 then 1.000
12 0.917 if Crab flavor = 1 and Tomato flavor = 1 then 1.000
11 0.909 if Curry beef = 1 and Crab flavor = 1 then 1.000
10 0.9 if spices salt = 1 and Sauced beef flavor = 1 then 1.000
10 0.9 if Crab flavor = 1 and Sauced beef flavor = 1 then 1.000
BBQ Flavor Rule Set
1.000 = BBQ Flavor
ID Probability Rule
12 1 if Chicken flavor = 1 and Cheese corn flavor = 1 then 1.000
12 1 if Chicken flavor = 1 and Kimchi flavor = 1 then 1.000
13 1 if Yolk = 1 then 1.000
13 1 if Chicken flavor = 1 and Hot sichuan = 1 then 1.000
13 1 if Chicken flavor = 1 and Sauced beef flavor = 1 then 1.000
14 1 if Chicken flavor = 1 then 1.000
14 1 if Chives flavor = 1 and Cheese corn flavor = 1 then 1.000
11 1 if Pork steak = 1 then 1.000
13 1 if Cumin BBQ = 1 then 1.000
11 1 if Pork steak = 1 and Yolk = 1 then 1.000
4 1 if Pork steak = 1 and Crab flavor = 1 then 1.000
11 1 if Pork steak = 1 and Cumin BBQ = 1 then 1.000
11 1 if Pork steak = 1 and Chicken flavor = 1 then 1.000
6 1 if Pork steak = 1 and Tomato flavor = 1 then 1.000
11 1 if Pork steak = 1 and Hot sichuan = 1 then 1.000
11 1 if Pork steak = 1 and Chives flavor = 1 then 1.000
10 1 if Pork steak = 1 and Sauced beef flavor = 1 then 1.000
9 1 if Pork steak = 1 and Cheese corn flavor = 1 then 1.000
9 1 if Pork steak = 1 and Kimchi flavor = 1 then 1.000
5 1 if Yolk = 1 and Crab flavor = 1 then 1.000
12 1 if Yolk = 1 and Cumin BBQ = 1 then 1.000
12 1 if Yolk = 1 and Chicken flavor = 1 then 1.000
7 1 if Yolk = 1 and Tomato flavor = 1 then 1.000
11 1 if Yolk = 1 and Hot sichuan = 1 then 1.000
12 1 if Yolk = 1 and Chives flavor = 1 then 1.000
115
11 1 if Yolk = 1 and Sauced beef flavor = 1 then 1.000
10 1 if Yolk = 1 and Cheese corn flavor = 1 then 1.000
10 1 if Yolk = 1 and Kimchi flavor = 1 then 1.000
6 1 if Crab flavor = 1 and Cumin BBQ = 1 then 1.000
4 1 if Cumin BBQ = 1 and Pepper beef steak = 1 then 1.000
13 1 if Cumin BBQ = 1 and Chicken flavor = 1 then 1.000
8 1 if Cumin BBQ = 1 and Tomato flavor = 1 then 1.000
12 1 if Cumin BBQ = 1 and Hot sichuan = 1 then 1.000
13 0.929 if Cumin BBQ = 1 and Chives flavor = 1 then 1.000
12 0.929 if Cumin BBQ = 1 and Sauced beef flavor = 1 then 1.000
11 0.923 if Cumin BBQ = 1 and Cheese corn flavor = 1 then 1.000
11 0.923 if Cumin BBQ = 1 and Kimchi flavor = 1 then 1.000
13 0.923 if Chicken flavor = 1 and Chives flavor = 1 then 1.000
13 0.917 if Hot sichuan = 1 and Chives flavor = 1 then 1.000
14 0.917 if Chives flavor = 1 and Sauced beef flavor = 1 then 1.000
Cheese Corn Flavor Rule Set
1.000 = Cheese Corn Flavor
ID Probability Rule
20 1 if Kimchi flavor = 1 then 1.000
10 1 if Yolk = 1 and Kimchi flavor = 1 then 1.000
10 1 if Crab flavor = 1 and Chives flavor = 1 then 1.000
10 1 if Crab flavor = 1 and Sauced beef flavor = 1 then 1.000
10 1 if Pepper beef steak = 1 and Sauced beef flavor = 1 then 1.000
11 1 if Cumin BBQ = 1 and Kimchi flavor = 1 then 1.000
12 1 if Curry beef = 1 and Kimchi flavor = 1 then 1.000
12 1 if spices salt = 1 and Kimchi flavor = 1 then 1.000
12 1 if Crab flavor = 1 and Kimchi flavor = 1 then 1.000
12 1 if Chicken flavor = 1 and Kimchi flavor = 1 then 1.000
12 1 if Tomato flavor = 1 and Chives flavor = 1 then 1.000
13 1 if Pepper beef steak = 1 and Kimchi flavor = 1 then 1.000
14 1 if Tomato flavor = 1 and Sauced beef flavor = 1 then 1.000
14 1 if Hot sichuan = 1 and Kimchi flavor = 1 then 1.000
15 1 if Tomato flavor = 1 and Kimchi flavor = 1 then 1.000
15 1 if Sauced beef flavor = 1 and Kimchi flavor = 1 then 1.000
16 1 if BBQ flavor = 1 and Kimchi flavor = 1 then 1.000
4 1 if Pork steak = 1 and Crab flavor = 1 then 1.000
6 1 if Pork steak = 1 and Tomato flavor = 1 then 1.000
5 0.938 if Yolk = 1 and Crab flavor = 1 then 1.000
7 0.933 if Yolk = 1 and Tomato flavor = 1 then 1.000
4 0.933 if Curry beef = 1 and Chicken flavor = 1 then 1.000
8 0.929 if Curry beef = 1 and BBQ flavor = 1 then 1.000
116
4 0.929 if spices salt = 1 and Chicken flavor = 1 then 1.000
8 0.923 if spices salt = 1 and BBQ flavor = 1 then 1.000
6 0.917 if Crab flavor = 1 and Cumin BBQ = 1 then 1.000
7 0.917 if Crab flavor = 1 and Chicken flavor = 1 then 1.000
7 0.917 if Crab flavor = 1 and Hot sichuan = 1 then 1.000
9 0.917 if Crab flavor = 1 and BBQ flavor = 1 then 1.000
4 0.917 if Cumin BBQ = 1 and Pepper beef steak = 1 then 1.000
8 0.909 if Cumin BBQ = 1 and Tomato flavor = 1 then 1.000
5 0.9 if Pepper beef steak = 1 and Chicken flavor = 1 then 1.000
9 0.9 if Pepper beef steak = 1 and BBQ flavor = 1 then 1.000
9 0.9 if Chicken flavor = 1 and Tomato flavor = 1 then 1.000
11 0.9 if Tomato flavor = 1 and Hot sichuan = 1 then 1.000
12 0.9 if Tomato flavor = 1 and BBQ flavor = 1 then 1.000
Sauced Beef Flavor Rule Set
1.000 = Sauced Beef Flavor
ID Probability Rule
6 1 if Pork steak = 1 and Tomato flavor = 1 then 1.000
7 1 if Yolk = 1 and Tomato flavor = 1 then 1.000
4 1 if Curry beef = 1 and Chicken flavor = 1 then 1.000
4 1 if spices salt = 1 and Chicken flavor = 1 then 1.000
4 1 if Cumin BBQ = 1 and Pepper beef steak = 1 then 1.000
8 1 if Cumin BBQ = 1 and Tomato flavor = 1 then 1.000
5 1 if Pepper beef steak = 1 and Chicken flavor = 1 then 1.000
9 1 if Chicken flavor = 1 and Tomato flavor = 1 then 1.000
14 0.929 if Chicken flavor = 1 then 1.000
13 0.923 if Cumin BBQ = 1 then 1.000
13 0.923 if Cumin BBQ = 1 and Chicken flavor = 1 then 1.000
13 0.923 if Cumin BBQ = 1 and Chives flavor = 1 then 1.000
13 0.923 if Cumin BBQ = 1 and BBQ flavor = 1 then 1.000
13 0.923 if Chicken flavor = 1 and Hot sichuan = 1 then 1.000
13 0.923 if Chicken flavor = 1 and Chives flavor = 1 then 1.000
13 0.923 if Chicken flavor = 1 and BBQ flavor = 1 then 1.000
13 0.923 if Hot sichuan = 1 and Chives flavor = 1 then 1.000
15 0.923 if Chives flavor = 1 and BBQ flavor = 1 then 1.000
12 0.917 if Yolk = 1 and Cumin BBQ = 1 then 1.000
12 0.917 if Yolk = 1 and Chicken flavor = 1 then 1.000
12 0.917 if Yolk = 1 and Chives flavor = 1 then 1.000
12 0.917 if Yolk = 1 and BBQ flavor = 1 then 1.000
12 0.917 if Cumin BBQ = 1 and Hot sichuan = 1 then 1.000
12 0.917 if Chicken flavor = 1 and Cheese corn flavor = 1 then 1.000
12 0.917 if Chicken flavor = 1 and Kimchi flavor = 1 then 1.000
117
12 0.917 if Tomato flavor = 1 and BBQ flavor = 1 then 1.000
11 0.909 if Pork steak = 1 then 1.000
11 0.909 if Pork steak = 1 and Yolk = 1 then 1.000
11 0.909 if Pork steak = 1 and Cumin BBQ = 1 then 1.000
11 0.909 if Pork steak = 1 and Chicken flavor = 1 then 1.000
11 0.909 if Pork steak = 1 and Hot sichuan = 1 then 1.000
11 0.909 if Pork steak = 1 and Chives flavor = 1 then 1.000
11 0.909 if Pork steak = 1 and BBQ flavor = 1 then 1.000
11 0.909 if Yolk = 1 and Hot sichuan = 1 then 1.000
11 0.909 if Cumin BBQ = 1 and Cheese corn flavor = 1 then 1.000
11 0.909 if Cumin BBQ = 1 and Kimchi flavor = 1 then 1.000
11 0.909 if Tomato flavor = 1 and Hot sichuan = 1 then 1.000
10 0.9 if Yolk = 1 and Cheese corn flavor = 1 then 1.000
10 0.9 if Yolk = 1 and Kimchi flavor = 1 then 1.000
Crab Flavor Rule Set
1.000 = Crab Flavor
ID Probability Rule
4 1 if Curry beef = 1 and Chicken flavor = 1 then 1.000
7 1 if Curry beef = 1 and Chives flavor = 1 then 1.000
4 1 if spices salt = 1 and Chicken flavor = 1 then 1.000
7 1 if spices salt = 1 and Chives flavor = 1 then 1.000
4 1 if Cumin BBQ = 1 and Pepper beef steak = 1 then 1.000
5 1 if Pepper beef steak = 1 and Chicken flavor = 1 then 1.000
8 1 if Pepper beef steak = 1 and Chives flavor = 1 then 1.000
10 0.9 if Pepper beef steak = 1 and Sauced beef flavor = 1 then 1.000
Tomato Flavor Rule Set
1.000 = Tomato Flavor
ID Probability Rule
4 1 if Curry beef = 1 and Chicken flavor = 1 then 1.000
7 1 if Curry beef = 1 and Chives flavor = 1 then 1.000
4 1 if spices salt = 1 and Chicken flavor = 1 then 1.000
7 1 if spices salt = 1 and Chives flavor = 1 then 1.000
4 1 if Cumin BBQ = 1 and Pepper beef steak = 1 then 1.000
5 1 if Pepper beef steak = 1 and Chicken flavor = 1 then 1.000
8 1 if Pepper beef steak = 1 and Chives flavor = 1 then 1.000
10 1 if Pepper beef steak = 1 and Sauced beef flavor = 1 then 1.000
13 0.923 if Pepper beef steak = 1 and Kimchi flavor = 1 then 1.000
12 0.917 if Curry beef = 1 and Kimchi flavor = 1 then 1.000
12 0.917 if spices salt = 1 and Kimchi flavor = 1 then 1.000
12 0.917 if Crab flavor = 1 and Pepper beef steak = 1 then 1.000
12 0.917 if Pepper beef steak = 1 and Cheese corn flavor = 1 then 1.000
118
11 0.909 if Curry beef = 1 and Crab flavor = 1 then 1.000
11 0.909 if Curry beef = 1 and Cheese corn flavor = 1 then 1.000
11 0.909 if spices salt = 1 and Cheese corn flavor = 1 then 1.000
10 0.9 if spices salt = 1 and Sauced beef flavor = 1 then 1.000
10 0.9 if Crab flavor = 1 and Sauced beef flavor = 1 then 1.000 Table 9 Scoring information for Top 10 Rules in South China Region Month Jan. Feb. Mar. Apr. May. Jun. Jul. Aug. Sep. Oct.
TF 1 0 0 1 0 0 1 1 1 0
CF 1 0 1 1 1 1 1 1 1 0
SBF 1 0 0 0 0 0 1 1 1 1
CCF 0 0 0 0 0 0 1 1 1 0
BQF 0 0 0 0 0 0 1 1 1 0
PBS 1 0 1 0 0 0 1 1 1 0
CKF 0 0 0 0 0 0 0 0 1 0
CBF 0 0 1 1 0 0 1 1 1 1
CBQ 0 0 0 0 0 0 0 0 1 0
HSS 1 0 1 0 0 1 1 1 1 0
PSF 0 0 0 0 0 0 0 0 0 0
YF 0 0 0 0 0 0 0 0 1 0
Kimchi flavor
0 0 0 0 0 0 1 1 1 0
Chives flavor 0 0 0 0 0 0 0 1 1 0
Hot sichuan 0 0 0 0 0 0 0 0 0 0
Scoring Information
Rule ID 1 CC TF PBS PBS CVF HSC HSS
Prediction 1 0.93 0.92 0.92 0.92 0.93 0.93 0.9
Confidence 1
367 249 250 213 377 20 182
Rule ID 2 KF HSS PSF
Prediction 2 0.92 0.92 0.92
Confidence 2
325 174 29
Rule ID 3 CBF KF
Prediction 3 0.92 0.92
Confidence 3
175 206
Table 10 Results for the Mid China
Consequent Antecedent Support % Confidence % Lift
1 CVF PSF 33.333 100 3
2 PSF CVF 33.333 100 3
3 Yolk PSF 33.333 100 2.769
119
4 BQF PSF 33.333 100 2.4 5 Yolk CVF 33.333 100 2.769
6 BQF CVF 33.333 100 2.4 7 HSS PBS 47.222 100 1.895
8 BQF Yolk 36.111 100 2.4
9 CKF CBQ 36.111 100 2.571 10 BQF CBQ 36.111 100 2.4
11 BQF CKF 38.889 100 2.4 12 HSS CBF and PBS 44.444 100 1.895
13 PBS CBF and CF 19.444 100 2.118
14 PBS CBF and CKF 11.111 100 2.118 15 PBS CBF and TF 22.222 100 2.118
16 PBS CBF and BQF 11.111 100 2.118 17 PBS CBF and HSC 25 100 2.118
18 PBS CBF and CCF 30.556 100 2.118 19 PBS CBF and KF 27.778 100 2.118
20 HSS CBF and CF 19.444 100 1.895
21 HSS CBF and CKF 11.111 100 1.895 22 HSS CBF and TF 22.222 100 1.895
23 HSS CBF and BQF 11.111 100 1.895 24 HSS CBF and HSC 25 100 1.895
25 HSS CBF and CCF 30.556 100 1.895
26 HSS CBF and KF 27.778 100 1.895 27 KF CBF and CF 19.444 100 1.895
28 TF CBF and CKF 11.111 100 2.25 29 BQF CBF and CKF 11.111 100 2.4
30 CKF CBF and BQF 11.111 100 2.571 31 CCF CBF and CKF 11.111 100 1.8
32 SBF CBF and CKF 11.111 100 1.8
33 TF CBF and BQF 11.111 100 2.25 34 CCF CBF and BQF 11.111 100 1.8
35 SBF CBF and BQF 11.111 100 1.8 36 CVF PSF and CF 19.444 100 3
37 PSF CVF and CF 19.444 100 3
38 Yolk PSF and CVF 33.333 100 2.769 39 CVF PSF and Yolk 33.333 100 3
40 PSF CVF and Yolk 33.333 100 3 41 CVF PSF and CBQ 30.556 100 3
42 PSF CVF and CBQ 30.556 100 3 43 CVF PSF and CKF 30.556 100 3
44 PSF CVF and CKF 30.556 100 3
120
45 CVF PSF and TF 22.222 100 3 46 PSF CVF and TF 22.222 100 3
47 BQF PSF and CVF 33.333 100 2.4 48 CVF PSF and BQF 33.333 100 3
49 PSF CVF and BQF 33.333 100 3
50 CVF PSF and HSC 30.556 100 3 51 PSF CVF and HSC 30.556 100 3
52 CVF PSF and CCF 25 100 3 53 PSF CVF and CCF 25 100 3
54 CVF PSF and SBF 25 100 3
55 PSF CVF and SBF 25 100 3 56 CVF PSF and KF 27.778 100 3
57 PSF CVF and KF 27.778 100 3 58 Yolk PSF and CF 19.444 100 2.769
59 PSF CF and Yolk 19.444 100 3 60 CBQ PSF and CF 19.444 100 2.769
61 CKF PSF and CF 19.444 100 2.571
62 BQF PSF and CF 19.444 100 2.4 63 HSC PSF and CF 19.444 100 1.895
64 SBF PSF and CF 19.444 100 1.8 65 KF PSF and CF 19.444 100 1.895
66 Yolk PSF and CBQ 30.556 100 2.769
67 Yolk PSF and CKF 30.556 100 2.769 68 Yolk PSF and TF 22.222 100 2.769
69 BQF PSF and Yolk 33.333 100 2.4 70 Yolk PSF and BQF 33.333 100 2.769
71 Yolk PSF and HSC 30.556 100 2.769 72 PSF Yolk and HSC 30.556 100 3
73 Yolk PSF and CCF 25 100 2.769
74 Yolk PSF and SBF 25 100 2.769 75 Yolk PSF and KF 27.778 100 2.769
76 CKF PSF and CBQ 30.556 100 2.571 77 CBQ PSF and CKF 30.556 100 2.769
78 CBQ PSF and TF 22.222 100 2.769
79 BQF PSF and CBQ 30.556 100 2.4 80 HSC PSF and CBQ 30.556 100 1.895
81 CBQ PSF and HSC 30.556 100 2.769 82 CBQ PSF and CCF 25 100 2.769
83 CBQ PSF and SBF 25 100 2.769 84 CBQ PSF and KF 27.778 100 2.769
85 CKF PSF and TF 22.222 100 2.571
121
86 BQF PSF and CKF 30.556 100 2.4 87 HSC PSF and CKF 30.556 100 1.895
88 CKF PSF and HSC 30.556 100 2.571 89 CKF PSF and CCF 25 100 2.571
90 CKF PSF and SBF 25 100 2.571
91 CKF PSF and KF 27.778 100 2.571 92 BQF PSF and TF 22.222 100 2.4
93 HSC PSF and TF 22.222 100 1.895 94 BQF PSF and HSC 30.556 100 2.4
95 BQF PSF and CCF 25 100 2.4
96 BQF PSF and SBF 25 100 2.4 97 BQF PSF and KF 27.778 100 2.4
98 HSC PSF and CCF 25 100 1.895 99 HSC PSF and SBF 25 100 1.895
100 HSC PSF and KF 27.778 100 1.895 101 KF PSF and CCF 25 100 1.895
102 KF PSF and SBF 25 100 1.895
103 Yolk CVF and CF 19.444 100 2.769 104 CVF CF and Yolk 19.444 100 3
105 CBQ CVF and CF 19.444 100 2.769 106 CKF CVF and CF 19.444 100 2.571
107 BQF CVF and CF 19.444 100 2.4
108 HSC CVF and CF 19.444 100 1.895 109 SBF CVF and CF 19.444 100 1.8
110 KF CVF and CF 19.444 100 1.895 111 Yolk CVF and CBQ 30.556 100 2.769
112 Yolk CVF and CKF 30.556 100 2.769 113 Yolk CVF and TF 22.222 100 2.769
114 BQF CVF and Yolk 33.333 100 2.4
115 Yolk CVF and BQF 33.333 100 2.769 116 Yolk CVF and HSC 30.556 100 2.769
117 CVF Yolk and HSC 30.556 100 3 118 Yolk CVF and CCF 25 100 2.769
119 Yolk CVF and SBF 25 100 2.769
120 Yolk CVF and KF 27.778 100 2.769 121 CKF CVF and CBQ 30.556 100 2.571
122 CBQ CVF and CKF 30.556 100 2.769 123 CBQ CVF and TF 22.222 100 2.769
124 BQF CVF and CBQ 30.556 100 2.4 125 HSC CVF and CBQ 30.556 100 1.895
126 CBQ CVF and HSC 30.556 100 2.769
122
127 CBQ CVF and CCF 25 100 2.769 128 CBQ CVF and SBF 25 100 2.769
129 CBQ CVF and KF 27.778 100 2.769 130 CKF CVF and TF 22.222 100 2.571
131 BQF CVF and CKF 30.556 100 2.4
132 HSC CVF and CKF 30.556 100 1.895 133 CKF CVF and HSC 30.556 100 2.571
134 CKF CVF and CCF 25 100 2.571 135 CKF CVF and SBF 25 100 2.571
136 CKF CVF and KF 27.778 100 2.571
137 BQF CVF and TF 22.222 100 2.4 138 HSC CVF and TF 22.222 100 1.895
139 BQF CVF and HSC 30.556 100 2.4 140 BQF CVF and CCF 25 100 2.4
141 BQF CVF and SBF 25 100 2.4 142 BQF CVF and KF 27.778 100 2.4
143 HSC CVF and CCF 25 100 1.895
144 HSC CVF and SBF 25 100 1.895 145 HSC CVF and KF 27.778 100 1.895
146 KF CVF and CCF 25 100 1.895 147 KF CVF and SBF 25 100 1.895
148 HSS PBS and CF 22.222 100 1.895
149 PBS HSS and CF 22.222 100 2.118 150 HSS PBS and CBQ 11.111 100 1.895
151 PBS HSS and CBQ 11.111 100 2.118 152 HSS PBS and CKF 13.889 100 1.895
153 PBS HSS and CKF 13.889 100 2.118 154 HSS PBS and TF 25 100 1.895
155 PBS HSS and TF 25 100 2.118
156 HSS PBS and BQF 13.889 100 1.895 157 PBS HSS and BQF 13.889 100 2.118
158 HSS PBS and HSC 27.778 100 1.895 159 PBS HSS and HSC 27.778 100 2.118
160 HSS PBS and CCF 33.333 100 1.895
161 PBS HSS and CCF 33.333 100 2.118 162 HSS PBS and SBF 30.556 100 1.895
163 HSS PBS and KF 30.556 100 1.895 164 PBS HSS and KF 30.556 100 2.118
165 KF PBS and CF 22.222 100 1.895 166 CKF PBS and CBQ 11.111 100 2.571
167 TF PBS and CBQ 11.111 100 2.25
123
168 BQF PBS and CBQ 11.111 100 2.4 169 CCF PBS and CBQ 11.111 100 1.8
170 SBF PBS and CBQ 11.111 100 1.8 171 KF PBS and CBQ 11.111 100 1.895
172 TF PBS and CKF 13.889 100 2.25
173 BQF PBS and CKF 13.889 100 2.4 174 CKF PBS and BQF 13.889 100 2.571
175 CCF PBS and CKF 13.889 100 1.8 176 SBF PBS and CKF 13.889 100 1.8
177 TF PBS and BQF 13.889 100 2.25
178 CCF PBS and BQF 13.889 100 1.8 179 SBF PBS and BQF 13.889 100 1.8
180 KF HSS and CF 22.222 100 1.895 181 CKF HSS and CBQ 11.111 100 2.571
182 TF HSS and CBQ 11.111 100 2.25 183 BQF HSS and CBQ 11.111 100 2.4
184 CCF HSS and CBQ 11.111 100 1.8
185 SBF HSS and CBQ 11.111 100 1.8 186 KF HSS and CBQ 11.111 100 1.895
187 TF HSS and CKF 13.889 100 2.25 188 BQF HSS and CKF 13.889 100 2.4
189 CKF HSS and BQF 13.889 100 2.571
190 CCF HSS and CKF 13.889 100 1.8 191 SBF HSS and CKF 13.889 100 1.8
192 TF HSS and BQF 13.889 100 2.25 193 CCF HSS and BQF 13.889 100 1.8
194 SBF HSS and BQF 13.889 100 1.8 195 CBQ CF and Yolk 19.444 100 2.769
196 CKF CF and Yolk 19.444 100 2.571
197 BQF CF and Yolk 19.444 100 2.4 198 HSC CF and Yolk 19.444 100 1.895
199 SBF CF and Yolk 19.444 100 1.8 200 KF CF and Yolk 19.444 100 1.895
201 CKF CF and CBQ 22.222 100 2.571
202 CBQ CF and CKF 22.222 100 2.769 203 BQF CF and CBQ 22.222 100 2.4
204 CBQ CF and BQF 22.222 100 2.769 205 HSC CF and CBQ 22.222 100 1.895
206 SBF CF and CBQ 22.222 100 1.8 207 KF CF and CBQ 22.222 100 1.895
208 BQF CF and CKF 22.222 100 2.4
124
209 CKF CF and BQF 22.222 100 2.571 210 HSC CF and CKF 22.222 100 1.895
211 SBF CF and CKF 22.222 100 1.8 212 KF CF and CKF 22.222 100 1.895
213 HSC CF and TF 25 100 1.895
214 SBF CF and TF 25 100 1.8 215 KF CF and TF 25 100 1.895
216 HSC CF and BQF 22.222 100 1.895 217 SBF CF and BQF 22.222 100 1.8
218 KF CF and BQF 22.222 100 1.895
219 KF CF and HSC 30.556 100 1.895 220 KF CF and CCF 27.778 100 1.895
221 KF CF and SBF 33.333 100 1.895 222 CKF Yolk and CBQ 33.333 100 2.571
223 CBQ Yolk and CKF 33.333 100 2.769 224 CBQ Yolk and TF 25 100 2.769
225 BQF Yolk and CBQ 33.333 100 2.4
226 CBQ Yolk and HSC 30.556 100 2.769 227 CBQ Yolk and CCF 27.778 100 2.769
228 CBQ Yolk and SBF 27.778 100 2.769 229 CBQ Yolk and KF 30.556 100 2.769
230 CKF Yolk and TF 25 100 2.571
231 BQF Yolk and CKF 33.333 100 2.4 232 CKF Yolk and HSC 30.556 100 2.571
233 CKF Yolk and CCF 27.778 100 2.571 234 CKF Yolk and SBF 27.778 100 2.571
235 CKF Yolk and KF 30.556 100 2.571 236 BQF Yolk and TF 25 100 2.4
237 BQF Yolk and HSC 30.556 100 2.4
238 BQF Yolk and CCF 27.778 100 2.4 239 BQF Yolk and SBF 27.778 100 2.4
240 BQF Yolk and KF 30.556 100 2.4 241 KF Yolk and CCF 27.778 100 1.895
242 KF Yolk and SBF 27.778 100 1.895
243 CKF CBQ and TF 27.778 100 2.571 244 BQF CBQ and CKF 36.111 100 2.4
245 CKF CBQ and BQF 36.111 100 2.571 246 CKF CBQ and HSC 33.333 100 2.571
247 CBQ CKF and HSC 33.333 100 2.769 248 CKF CBQ and CCF 30.556 100 2.571
249 CKF CBQ and SBF 30.556 100 2.571
125
250 CKF CBQ and KF 33.333 100 2.571 251 CBQ CKF and KF 33.333 100 2.769
252 BQF CBQ and TF 27.778 100 2.4 253 BQF CBQ and HSC 33.333 100 2.4
254 CBQ BQF and HSC 33.333 100 2.769
255 BQF CBQ and CCF 30.556 100 2.4 256 BQF CBQ and SBF 30.556 100 2.4
257 BQF CBQ and KF 33.333 100 2.4 258 CBQ BQF and KF 33.333 100 2.769
259 KF CBQ and CCF 30.556 100 1.895
260 KF CBQ and SBF 30.556 100 1.895 261 BQF CKF and TF 30.556 100 2.4
262 CKF TF and BQF 30.556 100 2.571 263 BQF CKF and HSC 33.333 100 2.4
264 CKF BQF and HSC 33.333 100 2.571 265 BQF CKF and CCF 33.333 100 2.4
266 CKF BQF and CCF 33.333 100 2.571
267 BQF CKF and SBF 33.333 100 2.4 268 CKF BQF and SBF 33.333 100 2.571
269 BQF CKF and KF 33.333 100 2.4 270 CKF BQF and KF 33.333 100 2.571
271 SBF TF and KF 33.333 100 1.8
272 KF HSC and SBF 38.889 100 1.895 273 HSS CBF 50 94.444 1.789
274 CBF PBS 47.222 94.118 1.882 275 PBS CBF and HSS 47.222 94.118 1.993
276 CBF PBS and HSS 47.222 94.118 1.882 277 CKF BQF 41.667 93.333 2.4
278 KF HSC and CCF 41.667 93.333 1.768
279 KF CCF and SBF 41.667 93.333 1.768 280 KF CF 38.889 92.857 1.759
281 CBQ CKF 38.889 92.857 2.571 282 CBQ CKF and BQF 38.889 92.857 2.571
283 PSF Yolk 36.111 92.308 2.769
284 CVF Yolk 36.111 92.308 2.769 285 CBQ Yolk 36.111 92.308 2.556
286 Yolk CBQ 36.111 92.308 2.556 287 CKF Yolk 36.111 92.308 2.374
288 HSC CBQ 36.111 92.308 1.749 289 KF CBQ 36.111 92.308 1.749
290 PSF Yolk and BQF 36.111 92.308 2.769
126
291 CVF Yolk and BQF 36.111 92.308 2.769 292 SBF CF and KF 36.111 92.308 1.662
293 Yolk CBQ and CKF 36.111 92.308 2.556 294 CBQ Yolk and BQF 36.111 92.308 2.556
295 Yolk CBQ and BQF 36.111 92.308 2.556
296 CKF Yolk and BQF 36.111 92.308 2.374 297 HSC CBQ and CKF 36.111 92.308 1.749
298 KF CBQ and CKF 36.111 92.308 1.749 299 HSC CBQ and BQF 36.111 92.308 1.749
300 KF CBQ and BQF 36.111 92.308 1.749
301 KF TF and SBF 36.111 92.308 1.749 302 CBQ PSF 33.333 91.667 2.538
303 CKF PSF 33.333 91.667 2.357 304 HSC PSF 33.333 91.667 1.737
305 CBQ CVF 33.333 91.667 2.538 306 CKF CVF 33.333 91.667 2.357
307 HSC CVF 33.333 91.667 1.737
308 CBF PBS and CCF 33.333 91.667 1.833 309 CBF HSS and CCF 33.333 91.667 1.833
310 HSS CBF and SBF 33.333 91.667 1.737 311 CBF HSS and SBF 33.333 91.667 1.833
312 CBQ PSF and CVF 33.333 91.667 2.538
313 CKF PSF and CVF 33.333 91.667 2.357 314 HSC PSF and CVF 33.333 91.667 1.737
315 CBQ PSF and Yolk 33.333 91.667 2.538 316 PSF Yolk and CBQ 33.333 91.667 2.75
317 CKF PSF and Yolk 33.333 91.667 2.357 318 PSF Yolk and CKF 33.333 91.667 2.75
319 HSC PSF and Yolk 33.333 91.667 1.737
320 CBQ PSF and BQF 33.333 91.667 2.538 321 PSF CBQ and HSC 33.333 91.667 2.75
322 CKF PSF and BQF 33.333 91.667 2.357 323 PSF CKF and HSC 33.333 91.667 2.75
324 HSC PSF and BQF 33.333 91.667 1.737
325 PSF BQF and HSC 33.333 91.667 2.75 326 CBQ CVF and Yolk 33.333 91.667 2.538
327 CVF Yolk and CBQ 33.333 91.667 2.75 328 CKF CVF and Yolk 33.333 91.667 2.357
329 CVF Yolk and CKF 33.333 91.667 2.75 330 HSC CVF and Yolk 33.333 91.667 1.737
331 CBQ CVF and BQF 33.333 91.667 2.538
127
332 CVF CBQ and HSC 33.333 91.667 2.75 333 CKF CVF and BQF 33.333 91.667 2.357
334 CVF CKF and HSC 33.333 91.667 2.75 335 HSC CVF and BQF 33.333 91.667 1.737
336 CVF BQF and HSC 33.333 91.667 2.75
337 PBS HSS and SBF 33.333 91.667 1.941 338 HSC Yolk and CBQ 33.333 91.667 1.737
339 Yolk CBQ and HSC 33.333 91.667 2.538 340 KF Yolk and CBQ 33.333 91.667 1.737
341 Yolk CBQ and KF 33.333 91.667 2.538
342 HSC Yolk and CKF 33.333 91.667 1.737 343 Yolk CKF and HSC 33.333 91.667 2.538
344 KF Yolk and CKF 33.333 91.667 1.737 345 Yolk CKF and KF 33.333 91.667 2.538
346 Yolk BQF and HSC 33.333 91.667 2.538 347 Yolk BQF and KF 33.333 91.667 2.538
348 CBQ CKF and CCF 33.333 91.667 2.538
349 CBQ CKF and SBF 33.333 91.667 2.538 350 CBQ BQF and CCF 33.333 91.667 2.538
351 CBQ BQF and SBF 33.333 91.667 2.538 352 KF CBQ and HSC 33.333 91.667 1.737
353 HSC CBQ and KF 33.333 91.667 1.737
354 CCF CBQ and KF 33.333 91.667 1.65 355 SBF CBQ and KF 33.333 91.667 1.65
356 KF CKF and HSC 33.333 91.667 1.737 357 HSC CKF and KF 33.333 91.667 1.737
358 SBF CKF and CCF 33.333 91.667 1.65 359 CCF CKF and SBF 33.333 91.667 1.65
360 KF CKF and CCF 33.333 91.667 1.737
361 CCF CKF and KF 33.333 91.667 1.65 362 KF CKF and SBF 33.333 91.667 1.737
363 SBF CKF and KF 33.333 91.667 1.65 364 SBF TF and HSC 33.333 91.667 1.65
365 KF TF and HSC 33.333 91.667 1.737
366 HSC TF and KF 33.333 91.667 1.737 367 KF BQF and HSC 33.333 91.667 1.737
368 HSC BQF and KF 33.333 91.667 1.737 369 SBF BQF and CCF 33.333 91.667 1.65
370 CCF BQF and SBF 33.333 91.667 1.65 371 KF BQF and CCF 33.333 91.667 1.737
372 CCF BQF and KF 33.333 91.667 1.65
128
373 KF BQF and SBF 33.333 91.667 1.737 374 SBF BQF and KF 33.333 91.667 1.65
375 CBF PBS and SBF 30.556 90.909 1.818 376 CBF PBS and KF 30.556 90.909 1.818
377 CBF HSS and KF 30.556 90.909 1.818
378 PSF Yolk and KF 30.556 90.909 2.727 379 KF PSF and CBQ 30.556 90.909 1.722
380 KF PSF and CKF 30.556 90.909 1.722 381 KF PSF and HSC 30.556 90.909 1.722
382 CVF Yolk and KF 30.556 90.909 2.727
383 KF CVF and CBQ 30.556 90.909 1.722 384 KF CVF and CKF 30.556 90.909 1.722
385 KF CVF and HSC 30.556 90.909 1.722 386 KF PBS and SBF 30.556 90.909 1.722
387 SBF PBS and KF 30.556 90.909 1.636 388 SBF HSS and KF 30.556 90.909 1.636
389 SBF CF and HSC 30.556 90.909 1.636
390 Yolk CBQ and CCF 30.556 90.909 2.517 391 Yolk CBQ and SBF 30.556 90.909 2.517
392 KF Yolk and HSC 30.556 90.909 1.722 393 HSC Yolk and KF 30.556 90.909 1.722
394 CCF Yolk and KF 30.556 90.909 1.636
395 SBF Yolk and KF 30.556 90.909 1.636 396 CBQ CKF and TF 30.556 90.909 2.517
397 CBQ TF and BQF 30.556 90.909 2.517 398 HSC CBQ and CCF 30.556 90.909 1.722
399 HSC CBQ and SBF 30.556 90.909 1.722 400 SBF CBQ and CCF 30.556 90.909 1.636
401 CCF CBQ and SBF 30.556 90.909 1.636
402 SBF CKF and TF 30.556 90.909 1.636 403 SBF TF and BQF 30.556 90.909 1.636
404 CBF PBS and HSC 27.778 90 1.8 405 CBF HSS and HSC 27.778 90 1.8
406 SBF CBF and KF 27.778 90 1.62
407 PSF Yolk and CCF 27.778 90 2.7 408 PSF Yolk and SBF 27.778 90 2.7
409 CCF PSF and KF 27.778 90 1.62 410 SBF PSF and KF 27.778 90 1.62
411 CVF Yolk and CCF 27.778 90 2.7 412 CVF Yolk and SBF 27.778 90 2.7
413 CCF CVF and KF 27.778 90 1.62
129
414 SBF CVF and KF 27.778 90 1.62 415 HSC CF and CCF 27.778 90 1.705
416 SBF CF and CCF 27.778 90 1.62 417 Yolk CBQ and TF 27.778 90 2.492
418 HSC Yolk and CCF 27.778 90 1.705
419 HSC Yolk and SBF 27.778 90 1.705 420 SBF Yolk and CCF 27.778 90 1.62
421 CCF Yolk and SBF 27.778 90 1.62 422 HSC CBQ and TF 27.778 90 1.705
423 SBF CBQ and TF 27.778 90 1.62
424 KF CBQ and TF 27.778 90 1.705 Table 11 Scoring for All Rule Sets (Mid China Region)
Tomato Flavor Rule Set
1.000 = Tomato Flavor
ID Probability Rule
4 1 if Curry beef = 1 and Chicken flavor = 1 then 1.000
4 1 if Curry beef = 1 and BBQ flavor = 1 then 1.000
4 1 if Pepper beef steak = 1 and Cumin BBQ = 1 then 1.000
5 1 if Pepper beef steak = 1 and Chicken flavor = 1 then 1.000
5 1 if Pepper beef steak = 1 and BBQ flavor = 1 then 1.000
4 1 if spices salt = 1 and Cumin BBQ = 1 then 1.000
5 1 if spices salt = 1 and Chicken flavor = 1 then 1.000
5 1 if spices salt = 1 and BBQ flavor = 1 then 1.000
Hot & Spice Sichuan Flavor Rule Set
1.000 = Hot & Spice Sichuan Flavor
ID Probability Rule
10 1 if Crab flavor = 1 and Cheese corn flavor = 1 then 1.000
10 1 if Yolk = 1 and Cheese corn flavor = 1 then 1.000
10 1 if Yolk = 1 and Sauced beef flavor = 1 then 1.000
10 1 if Cumin BBQ = 1 and Tomato flavor = 1 then 1.000
11 1 if Yolk = 1 and Kimchi flavor = 1 then 1.000
11 1 if Cumin BBQ = 1 and Cheese corn flavor = 1 then 1.000
11 1 if Cumin BBQ = 1 and Sauced beef flavor = 1 then 1.000
12 1 if Pork steak = 1 then 1.000
12 1 if Chives flavor = 1 then 1.000
12 1 if Pork steak = 1 and Chives flavor = 1 then 1.000
12 1 if Pork steak = 1 and Yolk = 1 then 1.000
12 1 if Pork steak = 1 and BBQ flavor = 1 then 1.000
12 1 if Chives flavor = 1 and Yolk = 1 then 1.000
12 1 if Chives flavor = 1 and BBQ flavor = 1 then 1.000
130
12 1 if Yolk = 1 and Cumin BBQ = 1 then 1.000
12 1 if Yolk = 1 and Chicken flavor = 1 then 1.000
12 1 if Cumin BBQ = 1 and Kimchi flavor = 1 then 1.000
12 1 if Chicken flavor = 1 and Kimchi flavor = 1 then 1.000
12 1 if Tomato flavor = 1 and Kimchi flavor = 1 then 1.000
12 0.923 if BBQ flavor = 1 and Kimchi flavor = 1 then 1.000
13 0.923 if Cumin BBQ = 1 then 1.000
13 0.923 if Cumin BBQ = 1 and Chicken flavor = 1 then 1.000
13 0.917 if Cumin BBQ = 1 and BBQ flavor = 1 then 1.000
7 0.917 if Pork steak = 1 and Crab flavor = 1 then 1.000
11 0.917 if Pork steak = 1 and Cumin BBQ = 1 then 1.000
11 0.917 if Pork steak = 1 and Chicken flavor = 1 then 1.000
8 0.917 if Pork steak = 1 and Tomato flavor = 1 then 1.000
9 0.917 if Pork steak = 1 and Cheese corn flavor = 1 then 1.000
9 0.917 if Pork steak = 1 and Sauced beef flavor = 1 then 1.000
10 0.917 if Pork steak = 1 and Kimchi flavor = 1 then 1.000
7 0.917 if Chives flavor = 1 and Crab flavor = 1 then 1.000
11 0.917 if Chives flavor = 1 and Cumin BBQ = 1 then 1.000
11 0.917 if Chives flavor = 1 and Chicken flavor = 1 then 1.000
8 0.917 if Chives flavor = 1 and Tomato flavor = 1 then 1.000
9 0.917 if Chives flavor = 1 and Cheese corn flavor = 1 then 1.000
9 0.909 if Chives flavor = 1 and Sauced beef flavor = 1 then 1.000
10 0.909 if Chives flavor = 1 and Kimchi flavor = 1 then 1.000
7 0.909 if Crab flavor = 1 and Yolk = 1 then 1.000
8 0.9 if Crab flavor = 1 and Cumin BBQ = 1 then 1.000
8 0.9 if Crab flavor = 1 and Chicken flavor = 1 then 1.000
9 0.9 if Crab flavor = 1 and Tomato flavor = 1 then 1.000
8 0.9 if Crab flavor = 1 and BBQ flavor = 1 then 1.000
Chives Flavor Rule Set
1.000 = Chives Flavor
ID Probability Rule
12 1 if Pork steak = 1 then 1.000
7 1 if Pork steak = 1 and Crab flavor = 1 then 1.000
12 1 if Pork steak = 1 and Yolk = 1 then 1.000
11 1 if Pork steak = 1 and Cumin BBQ = 1 then 1.000
11 1 if Pork steak = 1 and Chicken flavor = 1 then 1.000
8 1 if Pork steak = 1 and Tomato flavor = 1 then 1.000
12 1 if Pork steak = 1 and BBQ flavor = 1 then 1.000
11 1 if Pork steak = 1 and Hot sichuan = 1 then 1.000
9 1 if Pork steak = 1 and Cheese corn flavor = 1 then 1.000
9 1 if Pork steak = 1 and Sauced beef flavor = 1 then 1.000
131
10 1 if Pork steak = 1 and Kimchi flavor = 1 then 1.000
7 1 if Crab flavor = 1 and Yolk = 1 then 1.000
11 1 if Yolk = 1 and Hot sichuan = 1 then 1.000
13 0.923 if Yolk = 1 then 1.000
13 0.923 if Yolk = 1 and BBQ flavor = 1 then 1.000
12 0.917 if Yolk = 1 and Cumin BBQ = 1 then 1.000
12 0.917 if Yolk = 1 and Chicken flavor = 1 then 1.000
12 0.917 if Cumin BBQ = 1 and Hot sichuan = 1 then 1.000
12 0.917 if Chicken flavor = 1 and Hot sichuan = 1 then 1.000
12 0.917 if BBQ flavor = 1 and Hot sichuan = 1 then 1.000
11 0.909 if Yolk = 1 and Kimchi flavor = 1 then 1.000
10 0.9 if Yolk = 1 and Cheese corn flavor = 1 then 1.000
10 0.9 if Yolk = 1 and Sauced beef flavor = 1 then 1.000
Kimchi Flavor Rule Set
1.000 = Kimchi Flavor
ID Probability Rule
7 1 if Curry beef = 1 and Crab flavor = 1 then 1.000
7 1 if Pork steak = 1 and Crab flavor = 1 then 1.000
9 1 if Pork steak = 1 and Cheese corn flavor = 1 then 1.000
9 1 if Pork steak = 1 and Sauced beef flavor = 1 then 1.000
7 1 if Chives flavor = 1 and Crab flavor = 1 then 1.000
9 1 if Chives flavor = 1 and Cheese corn flavor = 1 then 1.000
9 1 if Chives flavor = 1 and Sauced beef flavor = 1 then 1.000
8 1 if Pepper beef steak = 1 and Crab flavor = 1 then 1.000
4 1 if Pepper beef steak = 1 and Cumin BBQ = 1 then 1.000
8 1 if spices salt = 1 and Crab flavor = 1 then 1.000
4 1 if spices salt = 1 and Cumin BBQ = 1 then 1.000
7 1 if Crab flavor = 1 and Yolk = 1 then 1.000
8 1 if Crab flavor = 1 and Cumin BBQ = 1 then 1.000
8 1 if Crab flavor = 1 and Chicken flavor = 1 then 1.000
9 1 if Crab flavor = 1 and Tomato flavor = 1 then 1.000
8 1 if Crab flavor = 1 and BBQ flavor = 1 then 1.000
11 1 if Crab flavor = 1 and Hot sichuan = 1 then 1.000
10 1 if Crab flavor = 1 and Cheese corn flavor = 1 then 1.000
12 1 if Crab flavor = 1 and Sauced beef flavor = 1 then 1.000
10 1 if Yolk = 1 and Cheese corn flavor = 1 then 1.000
10 1 if Yolk = 1 and Sauced beef flavor = 1 then 1.000
11 1 if Cumin BBQ = 1 and Cheese corn flavor = 1 then 1.000
11 1 if Cumin BBQ = 1 and Sauced beef flavor = 1 then 1.000
14 1 if Hot sichuan = 1 and Sauced beef flavor = 1 then 1.000
15 0.933 if Hot sichuan = 1 and Cheese corn flavor = 1 then 1.000
132
15 0.933 if Cheese corn flavor = 1 and Sauced beef flavor = 1 then 1.000
14 0.929 if Crab flavor = 1 then 1.000
13 0.923 if Cumin BBQ = 1 then 1.000
13 0.923 if Cumin BBQ = 1 and Chicken flavor = 1 then 1.000
13 0.923 if Cumin BBQ = 1 and BBQ flavor = 1 then 1.000
13 0.923 if Tomato flavor = 1 and Sauced beef flavor = 1 then 1.000
12 0.917 if Yolk = 1 and Cumin BBQ = 1 then 1.000
12 0.917 if Yolk = 1 and Chicken flavor = 1 then 1.000
12 0.917 if Cumin BBQ = 1 and Hot sichuan = 1 then 1.000
12 0.917 if Chicken flavor = 1 and Hot sichuan = 1 then 1.000
12 0.917 if Chicken flavor = 1 and Cheese corn flavor = 1 then 1.000
12 0.917 if Chicken flavor = 1 and Sauced beef flavor = 1 then 1.000
12 0.917 if Tomato flavor = 1 and Hot sichuan = 1 then 1.000
12 0.917 if BBQ flavor = 1 and Hot sichuan = 1 then 1.000
12 0.917 if BBQ flavor = 1 and Cheese corn flavor = 1 then 1.000
12 0.917 if BBQ flavor = 1 and Sauced beef flavor = 1 then 1.000
11 0.909 if Pork steak = 1 and Cumin BBQ = 1 then 1.000
11 0.909 if Pork steak = 1 and Chicken flavor = 1 then 1.000
11 0.909 if Pork steak = 1 and Hot sichuan = 1 then 1.000
11 0.909 if Chives flavor = 1 and Cumin BBQ = 1 then 1.000
11 0.909 if Chives flavor = 1 and Chicken flavor = 1 then 1.000
11 0.909 if Chives flavor = 1 and Hot sichuan = 1 then 1.000
11 0.909 if Pepper beef steak = 1 and Sauced beef flavor = 1 then 1.000
11 0.909 if Yolk = 1 and Hot sichuan = 1 then 1.000
10 0.9 if Cumin BBQ = 1 and Tomato flavor = 1 then 1.000
Yolk Flavor Rule Set
1.000 = Yolk Flavor
ID Probability Rule
12 1 if Pork steak = 1 then 1.000
12 1 if Chives flavor = 1 then 1.000
12 1 if Pork steak = 1 and Chives flavor = 1 then 1.000
7 1 if Pork steak = 1 and Crab flavor = 1 then 1.000
11 1 if Pork steak = 1 and Cumin BBQ = 1 then 1.000
11 1 if Pork steak = 1 and Chicken flavor = 1 then 1.000
8 1 if Pork steak = 1 and Tomato flavor = 1 then 1.000
12 1 if Pork steak = 1 and BBQ flavor = 1 then 1.000
11 1 if Pork steak = 1 and Hot sichuan = 1 then 1.000
9 1 if Pork steak = 1 and Cheese corn flavor = 1 then 1.000
9 1 if Pork steak = 1 and Sauced beef flavor = 1 then 1.000
10 1 if Pork steak = 1 and Kimchi flavor = 1 then 1.000
7 1 if Chives flavor = 1 and Crab flavor = 1 then 1.000
133
11 1 if Chives flavor = 1 and Cumin BBQ = 1 then 1.000
11 1 if Chives flavor = 1 and Chicken flavor = 1 then 1.000
8 1 if Chives flavor = 1 and Tomato flavor = 1 then 1.000
12 1 if Chives flavor = 1 and BBQ flavor = 1 then 1.000
11 1 if Chives flavor = 1 and Hot sichuan = 1 then 1.000
9 1 if Chives flavor = 1 and Cheese corn flavor = 1 then 1.000
9 1 if Chives flavor = 1 and Sauced beef flavor = 1 then 1.000
10 1 if Chives flavor = 1 and Kimchi flavor = 1 then 1.000
13 0.923 if Cumin BBQ = 1 then 1.000
13 0.923 if Cumin BBQ = 1 and Chicken flavor = 1 then 1.000
13 0.923 if Cumin BBQ = 1 and BBQ flavor = 1 then 1.000
12 0.917 if Cumin BBQ = 1 and Hot sichuan = 1 then 1.000
12 0.917 if Cumin BBQ = 1 and Kimchi flavor = 1 then 1.000
12 0.917 if Chicken flavor = 1 and Hot sichuan = 1 then 1.000
12 0.917 if Chicken flavor = 1 and Kimchi flavor = 1 then 1.000
12 0.917 if BBQ flavor = 1 and Hot sichuan = 1 then 1.000
12 0.917 if BBQ flavor = 1 and Kimchi flavor = 1 then 1.000
11 0.909 if Cumin BBQ = 1 and Cheese corn flavor = 1 then 1.000
11 0.909 if Cumin BBQ = 1 and Sauced beef flavor = 1 then 1.000
10 0.9 if Cumin BBQ = 1 and Tomato flavor = 1 then 1.000
Pork Steak Flavor Rule Set
1.000 = Pork Steak Flavor
ID Probability Rule
12 1 if Chives flavor = 1 then 1.000
7 1 if Chives flavor = 1 and Crab flavor = 1 then 1.000
12 1 if Chives flavor = 1 and Yolk = 1 then 1.000
11 1 if Chives flavor = 1 and Cumin BBQ = 1 then 1.000
11 1 if Chives flavor = 1 and Chicken flavor = 1 then 1.000
8 1 if Chives flavor = 1 and Tomato flavor = 1 then 1.000
12 1 if Chives flavor = 1 and BBQ flavor = 1 then 1.000
11 1 if Chives flavor = 1 and Hot sichuan = 1 then 1.000
9 1 if Chives flavor = 1 and Cheese corn flavor = 1 then 1.000
9 1 if Chives flavor = 1 and Sauced beef flavor = 1 then 1.000
10 1 if Chives flavor = 1 and Kimchi flavor = 1 then 1.000
7 1 if Crab flavor = 1 and Yolk = 1 then 1.000
11 1 if Yolk = 1 and Hot sichuan = 1 then 1.000
13 0.923 if Yolk = 1 then 1.000
13 0.923 if Yolk = 1 and BBQ flavor = 1 then 1.000
12 0.917 if Yolk = 1 and Cumin BBQ = 1 then 1.000
12 0.917 if Yolk = 1 and Chicken flavor = 1 then 1.000
12 0.917 if Cumin BBQ = 1 and Hot sichuan = 1 then 1.000
134
12 0.917 if Chicken flavor = 1 and Hot sichuan = 1 then 1.000
12 0.917 if BBQ flavor = 1 and Hot sichuan = 1 then 1.000
11 0.909 if Yolk = 1 and Kimchi flavor = 1 then 1.000
10 0.9 if Yolk = 1 and Cheese corn flavor = 1 then 1.000
10 0.9 if Yolk = 1 and Sauced beef flavor = 1 then 1.000
Hot & Spice Salt Flavor Rule Set
1.000 = Hot & Spice Salt Flavor
ID Probability Rule
17 1 if Pepper beef steak = 1 then 1.000
16 1 if Curry beef = 1 and Pepper beef steak = 1 then 1.000
7 1 if Curry beef = 1 and Crab flavor = 1 then 1.000
4 1 if Curry beef = 1 and Chicken flavor = 1 then 1.000
8 1 if Curry beef = 1 and Tomato flavor = 1 then 1.000
4 1 if Curry beef = 1 and BBQ flavor = 1 then 1.000
9 1 if Curry beef = 1 and Hot sichuan = 1 then 1.000
11 1 if Curry beef = 1 and Cheese corn flavor = 1 then 1.000
10 1 if Curry beef = 1 and Kimchi flavor = 1 then 1.000
8 1 if Pepper beef steak = 1 and Crab flavor = 1 then 1.000
4 1 if Pepper beef steak = 1 and Cumin BBQ = 1 then 1.000
5 1 if Pepper beef steak = 1 and Chicken flavor = 1 then 1.000
9 1 if Pepper beef steak = 1 and Tomato flavor = 1 then 1.000
5 1 if Pepper beef steak = 1 and BBQ flavor = 1 then 1.000
10 1 if Pepper beef steak = 1 and Hot sichuan = 1 then 1.000
12 1 if Pepper beef steak = 1 and Cheese corn flavor = 1 then 1.000
11 1 if Pepper beef steak = 1 and Sauced beef flavor = 1 then 1.000
11 1 if Pepper beef steak = 1 and Kimchi flavor = 1 then 1.000
18 0.944 if Curry beef = 1 then 1.000
12 0.917 if Curry beef = 1 and Sauced beef flavor = 1 then 1.000
Cumin BBQ Flavor Rule Set
1.000 = Cumin BBQ Flavor
ID Probability Rule
11 1 if Chicken flavor = 1 and Tomato flavor = 1 then 1.000
11 1 if Tomato flavor = 1 and BBQ flavor = 1 then 1.000
12 1 if Pork steak = 1 then 1.000
12 1 if Chives flavor = 1 then 1.000
12 1 if Pork steak = 1 and Chives flavor = 1 then 1.000
12 1 if Pork steak = 1 and Yolk = 1 then 1.000
12 1 if Pork steak = 1 and BBQ flavor = 1 then 1.000
12 1 if Chives flavor = 1 and Yolk = 1 then 1.000
12 1 if Chives flavor = 1 and BBQ flavor = 1 then 1.000
12 1 if Chicken flavor = 1 and Cheese corn flavor = 1 then 1.000
135
12 1 if Chicken flavor = 1 and Sauced beef flavor = 1 then 1.000
12 1 if BBQ flavor = 1 and Cheese corn flavor = 1 then 1.000
12 1 if BBQ flavor = 1 and Sauced beef flavor = 1 then 1.000
13 1 if Yolk = 1 then 1.000
13 1 if Yolk = 1 and BBQ flavor = 1 then 1.000
14 1 if Chicken flavor = 1 then 1.000
14 1 if Chicken flavor = 1 and BBQ flavor = 1 then 1.000
7 1 if Pork steak = 1 and Crab flavor = 1 then 1.000
11 1 if Pork steak = 1 and Chicken flavor = 1 then 1.000
8 1 if Pork steak = 1 and Tomato flavor = 1 then 1.000
11 1 if Pork steak = 1 and Hot sichuan = 1 then 1.000
9 1 if Pork steak = 1 and Cheese corn flavor = 1 then 1.000
9 1 if Pork steak = 1 and Sauced beef flavor = 1 then 1.000
10 1 if Pork steak = 1 and Kimchi flavor = 1 then 1.000
7 1 if Chives flavor = 1 and Crab flavor = 1 then 1.000
11 1 if Chives flavor = 1 and Chicken flavor = 1 then 1.000
8 1 if Chives flavor = 1 and Tomato flavor = 1 then 1.000
11 0.929 if Chives flavor = 1 and Hot sichuan = 1 then 1.000
9 0.929 if Chives flavor = 1 and Cheese corn flavor = 1 then 1.000
9 0.923 if Chives flavor = 1 and Sauced beef flavor = 1 then 1.000
10 0.923 if Chives flavor = 1 and Kimchi flavor = 1 then 1.000
7 0.917 if Crab flavor = 1 and Yolk = 1 then 1.000
8 0.917 if Crab flavor = 1 and Chicken flavor = 1 then 1.000
8 0.917 if Crab flavor = 1 and BBQ flavor = 1 then 1.000
12 0.917 if Yolk = 1 and Chicken flavor = 1 then 1.000
9 0.917 if Yolk = 1 and Tomato flavor = 1 then 1.000
11 0.917 if Yolk = 1 and Hot sichuan = 1 then 1.000
10 0.917 if Yolk = 1 and Cheese corn flavor = 1 then 1.000
10 0.917 if Yolk = 1 and Sauced beef flavor = 1 then 1.000
11 0.917 if Yolk = 1 and Kimchi flavor = 1 then 1.000
12 0.917 if Chicken flavor = 1 and Hot sichuan = 1 then 1.000
12 0.917 if Chicken flavor = 1 and Kimchi flavor = 1 then 1.000
12 0.909 if BBQ flavor = 1 and Hot sichuan = 1 then 1.000
12 0.909 if BBQ flavor = 1 and Kimchi flavor = 1 then 1.000
Curry Beef Flavor Rule Set
1.000 = Curry Beef Flavor
ID Probability Rule
17 0.941 if Pepper beef steak = 1 then 1.000
17 0.941 if Pepper beef steak = 1 and spices salt = 1 then 1.000
12 0.917 if Pepper beef steak = 1 and Cheese corn flavor = 1 then 1.000
12 0.917 if spices salt = 1 and Cheese corn flavor = 1 then 1.000
136
12 0.917 if spices salt = 1 and Sauced beef flavor = 1 then 1.000
11 0.909 if Pepper beef steak = 1 and Sauced beef flavor = 1 then 1.000
11 0.909 if Pepper beef steak = 1 and Kimchi flavor = 1 then 1.000
11 0.909 if spices salt = 1 and Kimchi flavor = 1 then 1.000
10 0.9 if Pepper beef steak = 1 and Hot sichuan = 1 then 1.000
10 0.9 if spices salt = 1 and Hot sichuan = 1 then 1.000
Chicken Flavor Rule Set
1.000 = Chicken Flavor
ID Probability Rule
13 1 if Cumin BBQ = 1 then 1.000
4 1 if Curry beef = 1 and BBQ flavor = 1 then 1.000
7 1 if Pork steak = 1 and Crab flavor = 1 then 1.000
11 1 if Pork steak = 1 and Cumin BBQ = 1 then 1.000
8 1 if Pork steak = 1 and Tomato flavor = 1 then 1.000
11 1 if Pork steak = 1 and Hot sichuan = 1 then 1.000
9 1 if Pork steak = 1 and Cheese corn flavor = 1 then 1.000
9 1 if Pork steak = 1 and Sauced beef flavor = 1 then 1.000
10 1 if Pork steak = 1 and Kimchi flavor = 1 then 1.000
7 1 if Chives flavor = 1 and Crab flavor = 1 then 1.000
11 1 if Chives flavor = 1 and Cumin BBQ = 1 then 1.000
8 1 if Chives flavor = 1 and Tomato flavor = 1 then 1.000
11 1 if Chives flavor = 1 and Hot sichuan = 1 then 1.000
9 1 if Chives flavor = 1 and Cheese corn flavor = 1 then 1.000
9 1 if Chives flavor = 1 and Sauced beef flavor = 1 then 1.000
10 1 if Chives flavor = 1 and Kimchi flavor = 1 then 1.000
4 1 if Pepper beef steak = 1 and Cumin BBQ = 1 then 1.000
5 1 if Pepper beef steak = 1 and BBQ flavor = 1 then 1.000
4 1 if spices salt = 1 and Cumin BBQ = 1 then 1.000
5 1 if spices salt = 1 and BBQ flavor = 1 then 1.000
7 1 if Crab flavor = 1 and Yolk = 1 then 1.000
8 1 if Crab flavor = 1 and Cumin BBQ = 1 then 1.000
8 1 if Crab flavor = 1 and BBQ flavor = 1 then 1.000
12 1 if Yolk = 1 and Cumin BBQ = 1 then 1.000
9 1 if Yolk = 1 and Tomato flavor = 1 then 1.000
11 1 if Yolk = 1 and Hot sichuan = 1 then 1.000
10 1 if Yolk = 1 and Cheese corn flavor = 1 then 1.000
10 1 if Yolk = 1 and Sauced beef flavor = 1 then 1.000
11 1 if Yolk = 1 and Kimchi flavor = 1 then 1.000
10 1 if Cumin BBQ = 1 and Tomato flavor = 1 then 1.000
13 1 if Cumin BBQ = 1 and BBQ flavor = 1 then 1.000
12 1 if Cumin BBQ = 1 and Hot sichuan = 1 then 1.000
137
11 1 if Cumin BBQ = 1 and Cheese corn flavor = 1 then 1.000
11 1 if Cumin BBQ = 1 and Sauced beef flavor = 1 then 1.000
12 1 if Cumin BBQ = 1 and Kimchi flavor = 1 then 1.000
11 1 if Tomato flavor = 1 and BBQ flavor = 1 then 1.000
12 1 if BBQ flavor = 1 and Hot sichuan = 1 then 1.000
12 1 if BBQ flavor = 1 and Cheese corn flavor = 1 then 1.000
12 1 if BBQ flavor = 1 and Sauced beef flavor = 1 then 1.000
12 1 if BBQ flavor = 1 and Kimchi flavor = 1 then 1.000
15 0.933 if BBQ flavor = 1 then 1.000
13 0.923 if Yolk = 1 then 1.000
13 0.923 if Yolk = 1 and BBQ flavor = 1 then 1.000
12 0.917 if Pork steak = 1 then 1.000
12 0.917 if Chives flavor = 1 then 1.000
12 0.917 if Pork steak = 1 and Chives flavor = 1 then 1.000
12 0.917 if Pork steak = 1 and Yolk = 1 then 1.000
12 0.917 if Pork steak = 1 and BBQ flavor = 1 then 1.000
12 0.917 if Chives flavor = 1 and Yolk = 1 then 1.000
12 0.917 if Chives flavor = 1 and BBQ flavor = 1 then 1.000
Pepper Beef Steak Flavor Rule Set
1.000 = Pepper Beef Steak Flavor
ID Probability Rule
7 1 if Curry beef = 1 and Crab flavor = 1 then 1.000
4 1 if Curry beef = 1 and Chicken flavor = 1 then 1.000
8 1 if Curry beef = 1 and Tomato flavor = 1 then 1.000
4 1 if Curry beef = 1 and BBQ flavor = 1 then 1.000
9 1 if Curry beef = 1 and Hot sichuan = 1 then 1.000
11 1 if Curry beef = 1 and Cheese corn flavor = 1 then 1.000
10 1 if Curry beef = 1 and Kimchi flavor = 1 then 1.000
8 1 if spices salt = 1 and Crab flavor = 1 then 1.000
4 1 if spices salt = 1 and Cumin BBQ = 1 then 1.000
5 1 if spices salt = 1 and Chicken flavor = 1 then 1.000
9 1 if spices salt = 1 and Tomato flavor = 1 then 1.000
5 1 if spices salt = 1 and BBQ flavor = 1 then 1.000
10 1 if spices salt = 1 and Hot sichuan = 1 then 1.000
12 1 if spices salt = 1 and Cheese corn flavor = 1 then 1.000
11 1 if spices salt = 1 and Kimchi flavor = 1 then 1.000
17 0.941 if Curry beef = 1 and spices salt = 1 then 1.000
12 0.917 if spices salt = 1 and Sauced beef flavor = 1 then 1.000
BBQ Flavor Rule Set
1.000 = BBQ Flavor
ID Probability Rule
138
12 1 if Pork steak = 1 then 1.000
11 1 if Pork steak = 1 and Cumin BBQ = 1 then 1.000
11 1 if Pork steak = 1 and Chicken flavor = 1 then 1.000
8 1 if Pork steak = 1 and Tomato flavor = 1 then 1.000
11 1 if Pork steak = 1 and Hot sichuan = 1 then 1.000
9 1 if Pork steak = 1 and Cheese corn flavor = 1 then 1.000
9 1 if Pork steak = 1 and Sauced beef flavor = 1 then 1.000
10 1 if Pork steak = 1 and Kimchi flavor = 1 then 1.000
7 1 if Chives flavor = 1 and Crab flavor = 1 then 1.000
12 1 if Chives flavor = 1 and Yolk = 1 then 1.000
11 1 if Chives flavor = 1 and Cumin BBQ = 1 then 1.000
12 1 if Chives flavor = 1 then 1.000
11 1 if Chives flavor = 1 and Chicken flavor = 1 then 1.000
8 1 if Chives flavor = 1 and Tomato flavor = 1 then 1.000
11 1 if Chives flavor = 1 and Hot sichuan = 1 then 1.000
9 1 if Chives flavor = 1 and Cheese corn flavor = 1 then 1.000
9 1 if Chives flavor = 1 and Sauced beef flavor = 1 then 1.000
10 1 if Chives flavor = 1 and Kimchi flavor = 1 then 1.000
4 1 if Pepper beef steak = 1 and Cumin BBQ = 1 then 1.000
5 1 if Pepper beef steak = 1 and Chicken flavor = 1 then 1.000
4 1 if spices salt = 1 and Cumin BBQ = 1 then 1.000
5 1 if spices salt = 1 and Chicken flavor = 1 then 1.000
13 1 if Yolk = 1 then 1.000
7 1 if Crab flavor = 1 and Yolk = 1 then 1.000
8 1 if Crab flavor = 1 and Cumin BBQ = 1 then 1.000
8 1 if Crab flavor = 1 and Chicken flavor = 1 then 1.000
12 1 if Yolk = 1 and Cumin BBQ = 1 then 1.000
12 1 if Yolk = 1 and Chicken flavor = 1 then 1.000
9 1 if Yolk = 1 and Tomato flavor = 1 then 1.000
11 1 if Yolk = 1 and Hot sichuan = 1 then 1.000
10 1 if Yolk = 1 and Cheese corn flavor = 1 then 1.000
10 1 if Yolk = 1 and Sauced beef flavor = 1 then 1.000
11 1 if Yolk = 1 and Kimchi flavor = 1 then 1.000
13 1 if Cumin BBQ = 1 then 1.000
13 1 if Cumin BBQ = 1 and Chicken flavor = 1 then 1.000
10 1 if Cumin BBQ = 1 and Tomato flavor = 1 then 1.000
12 1 if Cumin BBQ = 1 and Hot sichuan = 1 then 1.000
11 1 if Cumin BBQ = 1 and Cheese corn flavor = 1 then 1.000
11 1 if Cumin BBQ = 1 and Sauced beef flavor = 1 then 1.000
12 1 if Cumin BBQ = 1 and Kimchi flavor = 1 then 1.000
11 1 if Chicken flavor = 1 and Tomato flavor = 1 then 1.000
139
12 1 if Chicken flavor = 1 and Hot sichuan = 1 then 1.000
12 1 if Chicken flavor = 1 and Cheese corn flavor = 1 then 1.000
12 1 if Chicken flavor = 1 and Sauced beef flavor = 1 then 1.000
14 1 if Chicken flavor = 1 then 1.000
12 1 if Chicken flavor = 1 and Kimchi flavor = 1 then 1.000
4 1 if Curry beef = 1 and Chicken flavor = 1 then 1.000
12 1 if Pork steak = 1 and Chives flavor = 1 then 1.000
7 1 if Pork steak = 1 and Crab flavor = 1 then 1.000
12 1 if Pork steak = 1 and Yolk = 1 then 1.000
Cheese Corn Flavor Rule Set
1.000 = Cheese Corn Flavor
ID Probability Rule
4 1 if Curry beef = 1 and Chicken flavor = 1 then 1.000
4 1 if Curry beef = 1 and BBQ flavor = 1 then 1.000
4 1 if Pepper beef steak = 1 and Cumin BBQ = 1 then 1.000
5 1 if Pepper beef steak = 1 and Chicken flavor = 1 then 1.000
5 1 if Pepper beef steak = 1 and BBQ flavor = 1 then 1.000
4 1 if spices salt = 1 and Cumin BBQ = 1 then 1.000
5 1 if spices salt = 1 and Chicken flavor = 1 then 1.000
5 1 if spices salt = 1 and BBQ flavor = 1 then 1.000
12 0.917 if Cumin BBQ = 1 and Kimchi flavor = 1 then 1.000
12 0.917 if Chicken flavor = 1 and Sauced beef flavor = 1 then 1.000
12 0.917 if Chicken flavor = 1 and Kimchi flavor = 1 then 1.000
12 0.917 if BBQ flavor = 1 and Sauced beef flavor = 1 then 1.000
12 0.917 if BBQ flavor = 1 and Kimchi flavor = 1 then 1.000
11 0.909 if Yolk = 1 and Kimchi flavor = 1 then 1.000
11 0.909 if Cumin BBQ = 1 and Sauced beef flavor = 1 then 1.000
10 0.9 if Pork steak = 1 and Kimchi flavor = 1 then 1.000
10 0.9 if Chives flavor = 1 and Kimchi flavor = 1 then 1.000
10 0.9 if Yolk = 1 and Sauced beef flavor = 1 then 1.000
Sauced Beef Flavor Rule Set
1.000 = Sauced Beef Flavor
ID Probability Rule
12 1 if Tomato flavor = 1 and Kimchi flavor = 1 then 1.000
4 1 if Curry beef = 1 and Chicken flavor = 1 then 1.000
5 1 if Pepper beef steak = 1 and BBQ flavor = 1 then 1.000
4 1 if spices salt = 1 and Cumin BBQ = 1 then 1.000
5 1 if spices salt = 1 and Chicken flavor = 1 then 1.000
5 1 if spices salt = 1 and BBQ flavor = 1 then 1.000
7 1 if Crab flavor = 1 and Yolk = 1 then 1.000
8 1 if Crab flavor = 1 and Cumin BBQ = 1 then 1.000
140
8 1 if Crab flavor = 1 and Chicken flavor = 1 then 1.000
9 1 if Crab flavor = 1 and Tomato flavor = 1 then 1.000
4 1 if Curry beef = 1 and BBQ flavor = 1 then 1.000
8 1 if Crab flavor = 1 and BBQ flavor = 1 then 1.000
7 1 if Pork steak = 1 and Crab flavor = 1 then 1.000
7 1 if Chives flavor = 1 and Crab flavor = 1 then 1.000
4 1 if Pepper beef steak = 1 and Cumin BBQ = 1 then 1.000
5 1 if Pepper beef steak = 1 and Chicken flavor = 1 then 1.000
13 0.923 if Crab flavor = 1 and Kimchi flavor = 1 then 1.000
12 0.917 if Cumin BBQ = 1 and Kimchi flavor = 1 then 1.000
12 0.917 if Chicken flavor = 1 and Cheese corn flavor = 1 then 1.000
12 0.917 if Chicken flavor = 1 and Kimchi flavor = 1 then 1.000
12 0.917 if Tomato flavor = 1 and Hot sichuan = 1 then 1.000
12 0.917 if BBQ flavor = 1 and Cheese corn flavor = 1 then 1.000
12 0.917 if BBQ flavor = 1 and Kimchi flavor = 1 then 1.000
11 0.909 if Pepper beef steak = 1 and Kimchi flavor = 1 then 1.000
11 0.909 if spices salt = 1 and Kimchi flavor = 1 then 1.000
11 0.909 if Crab flavor = 1 and Hot sichuan = 1 then 1.000
11 0.909 if Yolk = 1 and Kimchi flavor = 1 then 1.000
11 0.909 if Cumin BBQ = 1 and Cheese corn flavor = 1 then 1.000
11 0.909 if Chicken flavor = 1 and Tomato flavor = 1 then 1.000
11 0.909 if Tomato flavor = 1 and BBQ flavor = 1 then 1.000
10 0.9 if Curry beef = 1 and Kimchi flavor = 1 then 1.000
10 0.9 if Pork steak = 1 and Kimchi flavor = 1 then 1.000
10 0.9 if Chives flavor = 1 and Kimchi flavor = 1 then 1.000
10 0.9 if Crab flavor = 1 and Cheese corn flavor = 1 then 1.000
10 0.9 if Yolk = 1 and Cheese corn flavor = 1 then 1.000
10 0.9 if Cumin BBQ = 1 and Tomato flavor = 1 then 1.000 Table 12 Scoring information for Top 10 Rules in Mid China Region Year 2013 2014 2015 2014 2015 2013 2015 2013 2014 2013
Month Jan May Sep Feb Jun Nov Mar Aug Dec May TF 0 0 1 0 0 0 1 1 1 0
CF 0 0 1 0 0 1 0 0 1 0
SBF 0 0 1 0 0 1 1 1 1 0 CCF 0 0 1 0 1 1 1 1 1 0
BQF 0 0 1 0 1 0 1 1 0 0 PSB 1 0 1 0 0 1 0 1 1 0
CKF 0 0 1 0 1 0 1 1 0 0 CF 1 0 1 0 0 1 0 1 1 0
CBQ 0 0 1 0 1 0 1 0 0 0
141
HSS 1 1 1 0 0 1 0 1 1 0 PSF 0 0 1 0 1 0 1 0 0 0
YF 0 0 1 0 1 0 1 0 0 0 KF 0 0 1 0 1 1 1 0 1 0
CVF 0 0 1 0 1 0 1 0 0 0
HSC 0 0 1 0 1 0 1 0 1 0 Prediction 1 SBF HSC KF
Condition 1 0.917 0.9 0.933 Rule ID 1 320 409 278
Prediction 2 CBQ Condition 2 0.929
Rule ID 2 281
Prediction 3 Condition 3
Rule ID 3 Table 13 Results for the East China Region
Consequent Antecedent Support % Confidence % Lift
1 CVF PSK 33.333 100 2.571
2 CKF PSK 33.333 100 2.571
3 CBQ PSK 33.333 100 2.571 4 BQF PSK 33.333 100 2.4
5 HSC PSK 33.333 100 1.895 6 BQF CBQ 38.889 100 2.4
7 PBS CBF 52.778 100 1.714 8 CVF PSK and CF 11.111 100 2.571
9 CKF PSK and CF 11.111 100 2.571
10 CBQ PSK and CF 11.111 100 2.571 11 TF PSK and CF 11.111 100 1.8
12 CF PSK and TF 11.111 100 2.25 13 BQF PSK and CF 11.111 100 2.4
14 SBF PSK and CF 11.111 100 1.895
15 HSC PSK and CF 11.111 100 1.895 16 CCF PSK and CF 11.111 100 2
17 KF PSK and CF 11.111 100 1.895 18 CVF PSK and Yolk 30.556 100 2.571
19 CKF PSK and Yolk 30.556 100 2.571 20 CBQ PSK and Yolk 30.556 100 2.571
21 BQF PSK and Yolk 30.556 100 2.4
22 HSC PSK and Yolk 30.556 100 1.895 23 PSK Yolk and HSC 30.556 100 3
142
24 CKF PSK and CVF 33.333 100 2.571 25 CVF PSK and CKF 33.333 100 2.571
26 CBQ PSK and CVF 33.333 100 2.571 27 CVF PSK and CBQ 33.333 100 2.571
28 CVF PSK and TF 11.111 100 2.571
29 BQF PSK and CVF 33.333 100 2.4 30 CVF PSK and BQF 33.333 100 2.571
31 CVF PSK and PBS 11.111 100 2.571 32 CVF PSK and SBF 16.667 100 2.571
33 HSC PSK and CVF 33.333 100 1.895
34 CVF PSK and HSC 33.333 100 2.571 35 CVF PSK and CCF 27.778 100 2.571
36 CVF PSK and KF 30.556 100 2.571 37 CBQ PSK and CKF 33.333 100 2.571
38 CKF PSK and CBQ 33.333 100 2.571 39 CKF PSK and TF 11.111 100 2.571
40 BQF PSK and CKF 33.333 100 2.4
41 CKF PSK and BQF 33.333 100 2.571 42 CKF PSK and PBS 11.111 100 2.571
43 CKF PSK and SBF 16.667 100 2.571 44 HSC PSK and CKF 33.333 100 1.895
45 CKF PSK and HSC 33.333 100 2.571
46 CKF PSK and CCF 27.778 100 2.571 47 CKF PSK and KF 30.556 100 2.571
48 CBQ PSK and TF 11.111 100 2.571 49 BQF PSK and CBQ 33.333 100 2.4
50 CBQ PSK and BQF 33.333 100 2.571 51 CBQ PSK and PBS 11.111 100 2.571
52 CBQ PSK and SBF 16.667 100 2.571
53 HSC PSK and CBQ 33.333 100 1.895 54 CBQ PSK and HSC 33.333 100 2.571
55 PSK CBQ and HSC 33.333 100 3 56 CBQ PSK and CCF 27.778 100 2.571
57 CBQ PSK and KF 30.556 100 2.571
58 BQF PSK and TF 11.111 100 2.4 59 SBF PSK and TF 11.111 100 1.895
60 HSC PSK and TF 11.111 100 1.895 61 CCF PSK and TF 11.111 100 2
62 KF PSK and TF 11.111 100 1.895 63 BQF PSK and PBS 11.111 100 2.4
64 BQF PSK and SBF 16.667 100 2.4
143
65 HSC PSK and BQF 33.333 100 1.895 66 BQF PSK and HSC 33.333 100 2.4
67 BQF PSK and CCF 27.778 100 2.4 68 BQF PSK and KF 30.556 100 2.4
69 SBF PSK and PBS 11.111 100 1.895
70 HSC PSK and PBS 11.111 100 1.895 71 CCF PSK and PBS 11.111 100 2
72 KF PSK and PBS 11.111 100 1.895 73 HSC PSK and SBF 16.667 100 1.895
74 CCF PSK and SBF 16.667 100 2
75 KF PSK and SBF 16.667 100 1.895 76 HSC PSK and CCF 27.778 100 1.895
77 HSC PSK and KF 30.556 100 1.895 78 KF PSK and CCF 27.778 100 1.895
79 TF CF and Yolk 13.889 100 1.8 80 SBF CF and Yolk 13.889 100 1.895
81 KF CF and Yolk 13.889 100 1.895
82 SBF CF and HSS 27.778 100 1.895 83 CKF CF and CVF 13.889 100 2.571
84 CBQ CF and CVF 13.889 100 2.571 85 CVF CF and CBQ 13.889 100 2.571
86 TF CF and CVF 13.889 100 1.8
87 CF CVF and TF 13.889 100 2.25 88 BQF CF and CVF 13.889 100 2.4
89 SBF CF and CVF 13.889 100 1.895 90 CCF CF and CVF 13.889 100 2
91 KF CF and CVF 13.889 100 1.895 92 CKF CF and CBQ 13.889 100 2.571
93 CF CKF and TF 13.889 100 2.25
94 CF CKF and CBF 13.889 100 2.25 95 SBF CF and CKF 16.667 100 1.895
96 CCF CF and CKF 16.667 100 2 97 KF CF and CKF 16.667 100 1.895
98 TF CF and CBQ 13.889 100 1.8
99 BQF CF and CBQ 13.889 100 2.4 100 SBF CF and CBQ 13.889 100 1.895
101 CCF CF and CBQ 13.889 100 2 102 KF CF and CBQ 13.889 100 1.895
103 TF CF and BQF 16.667 100 1.8 104 PBS CF and CBF 30.556 100 1.714
105 SBF CF and BQF 16.667 100 1.895
144
106 CCF CF and BQF 16.667 100 2 107 KF CF and BQF 16.667 100 1.895
108 SBF CF and CCF 25 100 1.895 109 SBF CF and KF 27.778 100 1.895
110 CKF Yolk and CVF 33.333 100 2.571
111 CVF Yolk and CKF 33.333 100 2.571 112 CBQ Yolk and CVF 33.333 100 2.571
113 BQF Yolk and CVF 33.333 100 2.4 114 CVF Yolk and HSC 30.556 100 2.571
115 CBQ Yolk and CKF 33.333 100 2.571
116 BQF Yolk and CKF 33.333 100 2.4 117 CKF Yolk and HSC 30.556 100 2.571
118 BQF Yolk and CBQ 36.111 100 2.4 119 CBQ Yolk and BQF 36.111 100 2.571
120 CBQ Yolk and HSC 30.556 100 2.571 121 CBQ Yolk and CCF 30.556 100 2.571
122 TF Yolk and CBF 13.889 100 1.8
123 SBF Yolk and TF 16.667 100 1.895 124 PBS Yolk and CBF 13.889 100 1.714
125 SBF Yolk and CBF 13.889 100 1.895 126 BQF Yolk and HSC 30.556 100 2.4
127 BQF Yolk and CCF 30.556 100 2.4
128 SBF Yolk and PBS 16.667 100 1.895 129 CCF HSS and CVF 13.889 100 2
130 KF HSS and CVF 13.889 100 1.895 131 CCF HSS and CKF 13.889 100 2
132 KF HSS and CKF 13.889 100 1.895 133 BQF HSS and CBQ 13.889 100 2.4
134 CCF HSS and CBQ 13.889 100 2
135 PBS HSS and CBF 44.444 100 1.714 136 CBF HSS and PBS 44.444 100 1.895
137 CCF HSS and BQF 16.667 100 2 138 CBQ CVF and CKF 36.111 100 2.571
139 CKF CVF and CBQ 36.111 100 2.571
140 CVF CKF and CBQ 36.111 100 2.571 141 CKF CVF and TF 13.889 100 2.571
142 CVF CKF and TF 13.889 100 2.571 143 BQF CVF and CKF 36.111 100 2.4
144 CKF CVF and BQF 36.111 100 2.571 145 CVF CKF and BQF 36.111 100 2.571
146 CBQ CVF and TF 13.889 100 2.571
145
147 BQF CVF and CBQ 36.111 100 2.4 148 CBQ CVF and BQF 36.111 100 2.571
149 CVF CBQ and HSC 33.333 100 2.571 150 CVF CBQ and KF 33.333 100 2.571
151 BQF CVF and TF 13.889 100 2.4
152 SBF CVF and TF 13.889 100 1.895 153 CCF CVF and TF 13.889 100 2
154 KF CVF and TF 13.889 100 1.895 155 PBS CVF and CBF 13.889 100 1.714
156 SBF CVF and CBF 13.889 100 1.895
157 CCF CVF and CBF 13.889 100 2 158 KF CVF and CBF 13.889 100 1.895
159 SBF CVF and PBS 16.667 100 1.895 160 CCF CVF and PBS 16.667 100 2
161 KF CVF and PBS 16.667 100 1.895 162 CCF CVF and SBF 22.222 100 2
163 KF CVF and SBF 22.222 100 1.895
164 KF CVF and CCF 33.333 100 1.895 165 CBQ CKF and TF 13.889 100 2.571
166 BQF CKF and CBQ 36.111 100 2.4 167 CBQ CKF and BQF 36.111 100 2.571
168 CKF CBQ and HSC 33.333 100 2.571
169 CKF CBQ and KF 33.333 100 2.571 170 BQF CKF and TF 13.889 100 2.4
171 SBF CKF and TF 13.889 100 1.895 172 CCF CKF and TF 13.889 100 2
173 KF CKF and TF 13.889 100 1.895 174 PBS CKF and CBF 13.889 100 1.714
175 SBF CKF and CBF 13.889 100 1.895
176 CCF CKF and CBF 13.889 100 2 177 KF CKF and CBF 13.889 100 1.895
178 SBF CKF and PBS 16.667 100 1.895 179 CCF CKF and PBS 16.667 100 2
180 KF CKF and PBS 16.667 100 1.895
181 CCF CKF and SBF 22.222 100 2 182 KF CKF and SBF 22.222 100 1.895
183 KF CKF and CCF 33.333 100 1.895 184 TF CBQ and CBF 13.889 100 1.8
185 BQF CBQ and TF 16.667 100 2.4 186 SBF CBQ and TF 16.667 100 1.895
187 CCF CBQ and TF 16.667 100 2
146
188 BQF CBQ and CBF 13.889 100 2.4 189 PBS CBQ and CBF 13.889 100 1.714
190 SBF CBQ and CBF 13.889 100 1.895 191 CCF CBQ and CBF 13.889 100 2
192 BQF CBQ and PBS 16.667 100 2.4
193 BQF CBQ and SBF 22.222 100 2.4 194 BQF CBQ and HSC 33.333 100 2.4
195 BQF CBQ and CCF 33.333 100 2.4 196 BQF CBQ and KF 33.333 100 2.4
197 SBF CBQ and PBS 16.667 100 1.895
198 CCF CBQ and PBS 16.667 100 2 199 CCF CBQ and SBF 22.222 100 2
200 TF CBF and BQF 16.667 100 1.8 201 PBS TF and CBF 41.667 100 1.714
202 CBF TF and PBS 41.667 100 1.895 203 SBF TF and BQF 19.444 100 1.895
204 CCF TF and BQF 19.444 100 2
205 SBF TF and CCF 25 100 1.895 206 PBS CBF and BQF 16.667 100 1.714
207 SBF CBF and BQF 16.667 100 1.895 208 CCF CBF and BQF 16.667 100 2
209 PBS CBF and SBF 36.111 100 1.714
210 PBS CBF and HSC 25 100 1.714 211 PBS CBF and CCF 30.556 100 1.714
212 PBS CBF and KF 30.556 100 1.714 213 SBF BQF and PBS 19.444 100 1.895
214 CCF BQF and PBS 19.444 100 2 215 CCF BQF and SBF 25 100 2
216 CCF SBF and HSC 30.556 100 2
217 CBQ BQF 41.667 93.333 2.4 218 KF HSC and CCF 41.667 93.333 1.768
219 HSC CCF and KF 41.667 93.333 1.768 220 CBQ Yolk 38.889 92.857 2.388
221 Yolk CBQ 38.889 92.857 2.388
222 BQF Yolk 38.889 92.857 2.229 223 CKF CVF 38.889 92.857 2.388
224 CVF CKF 38.889 92.857 2.388 225 CBQ CVF 38.889 92.857 2.388
226 CVF CBQ 38.889 92.857 2.388 227 BQF CVF 38.889 92.857 2.229
228 HSC CVF 38.889 92.857 1.759
147
229 KF CVF 38.889 92.857 1.759 230 CBQ CKF 38.889 92.857 2.388
231 CKF CBQ 38.889 92.857 2.388 232 BQF CKF 38.889 92.857 2.229
233 HSC CKF 38.889 92.857 1.759
234 KF CKF 38.889 92.857 1.759 235 SBF CF and TF 38.889 92.857 1.759
236 TF CF and SBF 38.889 92.857 1.671 237 CF TF and SBF 38.889 92.857 2.089
238 Yolk CBQ and BQF 38.889 92.857 2.388
239 CBF HSS and TF 38.889 92.857 1.759 240 PBS HSS and TF 38.889 92.857 1.592
241 CVF CBQ and BQF 38.889 92.857 2.388 242 CKF CBQ and BQF 38.889 92.857 2.388
243 CBF PBS and SBF 38.889 92.857 1.759 244 PSK CVF and CKF 36.111 92.308 2.769
245 PSK CVF and CBQ 36.111 92.308 2.769
246 PSK CVF and BQF 36.111 92.308 2.769 247 PSK CVF and HSC 36.111 92.308 2.769
248 PSK CKF and CBQ 36.111 92.308 2.769 249 PSK CKF and BQF 36.111 92.308 2.769
250 PSK CKF and HSC 36.111 92.308 2.769
251 PSK BQF and HSC 36.111 92.308 2.769 252 Yolk CVF and CKF 36.111 92.308 2.374
253 CVF Yolk and CBQ 36.111 92.308 2.374 254 Yolk CVF and CBQ 36.111 92.308 2.374
255 CVF Yolk and BQF 36.111 92.308 2.374 256 Yolk CVF and BQF 36.111 92.308 2.374
257 CKF Yolk and CBQ 36.111 92.308 2.374
258 Yolk CKF and CBQ 36.111 92.308 2.374 259 CKF Yolk and BQF 36.111 92.308 2.374
260 Yolk CKF and BQF 36.111 92.308 2.374 261 HSC CVF and CKF 36.111 92.308 1.749
262 CKF CVF and HSC 36.111 92.308 2.374
263 CVF CKF and HSC 36.111 92.308 2.374 264 KF CVF and CKF 36.111 92.308 1.749
265 CKF CVF and KF 36.111 92.308 2.374 266 CVF CKF and KF 36.111 92.308 2.374
267 HSC CVF and CBQ 36.111 92.308 1.749 268 CBQ CVF and HSC 36.111 92.308 2.374
269 KF CVF and CBQ 36.111 92.308 1.749
148
270 CBQ CVF and KF 36.111 92.308 2.374 271 HSC CVF and BQF 36.111 92.308 1.749
272 BQF CVF and HSC 36.111 92.308 2.215 273 CVF BQF and HSC 36.111 92.308 2.374
274 KF CVF and BQF 36.111 92.308 1.749
275 BQF CVF and KF 36.111 92.308 2.215 276 CVF BQF and KF 36.111 92.308 2.374
277 KF CVF and HSC 36.111 92.308 1.749 278 HSC CVF and KF 36.111 92.308 1.749
279 CCF CVF and KF 36.111 92.308 1.846
280 HSC CKF and CBQ 36.111 92.308 1.749 281 CBQ CKF and HSC 36.111 92.308 2.374
282 KF CKF and CBQ 36.111 92.308 1.749 283 CBQ CKF and KF 36.111 92.308 2.374
284 HSC CKF and BQF 36.111 92.308 1.749 285 BQF CKF and HSC 36.111 92.308 2.215
286 CKF BQF and HSC 36.111 92.308 2.374
287 KF CKF and BQF 36.111 92.308 1.749 288 BQF CKF and KF 36.111 92.308 2.215
289 CKF BQF and KF 36.111 92.308 2.374 290 KF CKF and HSC 36.111 92.308 1.749
291 HSC CKF and KF 36.111 92.308 1.749
292 CCF CKF and KF 36.111 92.308 1.846 293 CBQ BQF and HSC 36.111 92.308 2.374
294 CBQ BQF and CCF 36.111 92.308 2.374 295 CBQ BQF and KF 36.111 92.308 2.374
296 KF BQF and HSC 36.111 92.308 1.749 297 HSC BQF and KF 36.111 92.308 1.749
298 KF BQF and CCF 36.111 92.308 1.749
299 CCF BQF and KF 36.111 92.308 1.846 300 Yolk PSK 33.333 91.667 2.357
301 KF PSK 33.333 91.667 1.737 302 Yolk PSK and CVF 33.333 91.667 2.357
303 PSK Yolk and CVF 33.333 91.667 2.75
304 Yolk PSK and CKF 33.333 91.667 2.357 305 PSK Yolk and CKF 33.333 91.667 2.75
306 Yolk PSK and CBQ 33.333 91.667 2.357 307 Yolk PSK and BQF 33.333 91.667 2.357
308 Yolk PSK and HSC 33.333 91.667 2.357 309 KF PSK and CVF 33.333 91.667 1.737
310 KF PSK and CKF 33.333 91.667 1.737
149
311 KF PSK and CBQ 33.333 91.667 1.737 312 PSK CBQ and KF 33.333 91.667 2.75
313 KF PSK and BQF 33.333 91.667 1.737 314 KF PSK and HSC 33.333 91.667 1.737
315 CBF CF and PBS 33.333 91.667 1.737
316 HSC Yolk and CVF 33.333 91.667 1.737 317 KF Yolk and CVF 33.333 91.667 1.737
318 CVF Yolk and KF 33.333 91.667 2.357 319 HSC Yolk and CKF 33.333 91.667 1.737
320 KF Yolk and CKF 33.333 91.667 1.737
321 CKF Yolk and KF 33.333 91.667 2.357 322 Yolk CBQ and HSC 33.333 91.667 2.357
323 Yolk CBQ and CCF 33.333 91.667 2.357 324 CBQ Yolk and KF 33.333 91.667 2.357
325 Yolk CBQ and KF 33.333 91.667 2.357 326 BQF Yolk and KF 33.333 91.667 2.2
327 CBF HSS and SBF 33.333 91.667 1.737
328 PBS HSS and SBF 33.333 91.667 1.571 329 CKF CVF and CCF 33.333 91.667 2.357
330 CVF CKF and CCF 33.333 91.667 2.357 331 CBQ CVF and CCF 33.333 91.667 2.357
332 CVF CBQ and CCF 33.333 91.667 2.357
333 BQF CVF and CCF 33.333 91.667 2.2 334 HSC CVF and CCF 33.333 91.667 1.737
335 CBQ CKF and CCF 33.333 91.667 2.357 336 CKF CBQ and CCF 33.333 91.667 2.357
337 BQF CKF and CCF 33.333 91.667 2.2 338 HSC CKF and CCF 33.333 91.667 1.737
339 KF CBQ and HSC 33.333 91.667 1.737
340 HSC CBQ and KF 33.333 91.667 1.737 341 KF CBQ and CCF 33.333 91.667 1.737
342 CCF CBQ and KF 33.333 91.667 1.833 343 CBF PBS and CCF 33.333 91.667 1.737
344 CBF PBS and KF 33.333 91.667 1.737
345 SBF PBS and CCF 33.333 91.667 1.737 346 SBF PBS and KF 33.333 91.667 1.737
347 KF PSK and Yolk 30.556 90.909 1.722 348 Yolk PSK and KF 30.556 90.909 2.338
349 CCF PSK and KF 30.556 90.909 1.818 350 TF CF and CBF 30.556 90.909 1.636
351 SBF CF and CBF 30.556 90.909 1.722
150
352 CVF Yolk and CCF 30.556 90.909 2.338 353 CKF Yolk and CCF 30.556 90.909 2.338
354 KF Yolk and HSC 30.556 90.909 1.722 355 KF Yolk and CCF 30.556 90.909 1.722
356 CBF HSS and CCF 30.556 90.909 1.722
357 HSS CBF and CCF 30.556 90.909 1.722 358 CBF HSS and KF 30.556 90.909 1.722
359 HSS CBF and KF 30.556 90.909 1.722 360 PBS HSS and CCF 30.556 90.909 1.558
361 PBS HSS and KF 30.556 90.909 1.558
362 SBF CBF and CCF 30.556 90.909 1.722 363 SBF CBF and KF 30.556 90.909 1.722
364 KF SBF and HSC 30.556 90.909 1.722 365 CBF PBS 58.333 90.476 1.714
366 Yolk PSK and CCF 27.778 90 2.314 367 TF CF and HSS 27.778 90 1.62
368 CBF CF and HSS 27.778 90 1.705
369 PBS CF and HSS 27.778 90 1.543 370 TF CF and KF 27.778 90 1.62
371 CF TF and KF 27.778 90 2.025 372 CBF CF and KF 27.778 90 1.705
373 PBS CF and KF 27.778 90 1.543
374 CBF TF and KF 27.778 90 1.705 375 PBS TF and KF 27.778 90 1.543
376 SBF TF and KF 27.778 90 1.705 Table 14 Scoring for All Rule Sets (East China Region)
Hot & Spice Sichuan Flavor Rule Set
1.000 = Hot & Spice Sichuan Flavor
ID Probability Rule
4 1 if Pork steak = 1 and Tomato flavor = 1 then 1.000
12 1 if Pork steak = 1 and Cumin BBQ = 1 then 1.000
12 1 if Pork steak = 1 and Chicken flavor = 1 then 1.000
12 1 if Pork steak = 1 and Chives flavor = 1 then 1.000
11 1 if Pork steak = 1 and Yolk = 1 then 1.000
4 1 if Pork steak = 1 and Crab flavor = 1 then 1.000
11 1 if Pork steak = 1 and Kimchi flavor = 1 then 1.000
10 1 if Pork steak = 1 and Cheese corn flavor = 1 then 1.000
6 1 if Pork steak = 1 and Sauced beef flavor = 1 then 1.000
4 1 if Pork steak = 1 and Pepper beef steak = 1 then 1.000
12 1 if Pork steak = 1 and BBQ flavor = 1 then 1.000
12 1 if Pork steak = 1 then 1.000
151
15 0.933 if Cheese corn flavor = 1 and Kimchi flavor = 1 then 1.000
14 0.929 if Chicken flavor = 1 then 1.000
14 0.929 if Chives flavor = 1 then 1.000
13 0.923 if BBQ flavor = 1 and Kimchi flavor = 1 then 1.000
13 0.923 if Chicken flavor = 1 and Kimchi flavor = 1 then 1.000
13 0.923 if Chicken flavor = 1 and BBQ flavor = 1 then 1.000
13 0.923 if Chicken flavor = 1 and Cumin BBQ = 1 then 1.000
13 0.923 if Chives flavor = 1 and Kimchi flavor = 1 then 1.000
13 0.923 if Chives flavor = 1 and BBQ flavor = 1 then 1.000
13 0.923 if Chives flavor = 1 and Cumin BBQ = 1 then 1.000
13 0.923 if Chives flavor = 1 and Chicken flavor = 1 then 1.000
12 0.917 if Cumin BBQ = 1 and Kimchi flavor = 1 then 1.000
12 0.917 if Chicken flavor = 1 and Cheese corn flavor = 1 then 1.000
12 0.917 if Chives flavor = 1 and Cheese corn flavor = 1 then 1.000
12 0.917 if Yolk = 1 and Chicken flavor = 1 then 1.000
12 0.917 if Yolk = 1 and Chives flavor = 1 then 1.000
Hot & Spice Salt Flavor Rule Set
1.000 = Hot & Spice Salt Flavor
ID Probability Rule
11 0.909 if Curry beef = 1 and Cheese corn flavor = 1 then 1.000
11 0.909 if Curry beef = 1 and Kimchi flavor = 1 then 1.000
Yolk Flavor Rule Set
1.000 = Yolk Flavor
ID Probability Rule
14 0.929 if Cumin BBQ = 1 then 1.000
14 0.929 if Cumin BBQ = 1 and BBQ flavor = 1 then 1.000
13 0.923 if Chicken flavor = 1 and BBQ flavor = 1 then 1.000
13 0.923 if Chicken flavor = 1 and Cumin BBQ = 1 then 1.000
13 0.923 if Chives flavor = 1 and BBQ flavor = 1 then 1.000
13 0.923 if Chives flavor = 1 and Cumin BBQ = 1 then 1.000
13 0.923 if Chives flavor = 1 and Chicken flavor = 1 then 1.000
12 0.917 if Pork steak = 1 and Hot sichuan = 1 then 1.000
12 0.917 if Pork steak = 1 and BBQ flavor = 1 then 1.000
12 0.917 if Pork steak = 1 and Cumin BBQ = 1 then 1.000
12 0.917 if Pork steak = 1 and Chicken flavor = 1 then 1.000
12 0.917 if Pork steak = 1 and Chives flavor = 1 then 1.000
12 0.917 if Cumin BBQ = 1 and Kimchi flavor = 1 then 1.000
12 0.917 if Cumin BBQ = 1 and Cheese corn flavor = 1 then 1.000
12 0.917 if Cumin BBQ = 1 and Hot sichuan = 1 then 1.000
12 0.917 if Pork steak = 1 then 1.000
11 0.909 if Pork steak = 1 and Kimchi flavor = 1 then 1.000
152
10 0.9 if Pork steak = 1 and Cheese corn flavor = 1 then 1.000
Kimchi Flavor Rule Set
1.000 = Kimchi Flavor
ID Probability Rule
4 1 if Pork steak = 1 then 1.000
12 1 if Chives flavor = 1 then 1.000
8 1 if Yolk = 1 and Chicken flavor = 1 then 1.000
4 1 if Yolk = 1 and Hot sichuan = 1 then 1.000
6 1 if Yolk = 1 and Cheese corn flavor = 1 then 1.000
5 1 if spices salt = 1 and Chicken flavor = 1 then 1.000
5 1 if Chives flavor = 1 and Chicken flavor = 1 then 1.000
12 1 if Chives flavor = 1 and Tomato flavor = 1 then 1.000
8 1 if Chicken flavor = 1 then 1.000
6 1 if Chives flavor = 1 and BBQ flavor = 1 then 1.000
5 1 if Chives flavor = 1 and Hot sichuan = 1 then 1.000
5 1 if Chives flavor = 1 and Cheese corn flavor = 1 then 1.000
5 1 if Chicken flavor = 1 and Curry beef = 1 then 1.000
5 1 if Chicken flavor = 1 and BBQ flavor = 1 then 1.000
6 1 if Cumin BBQ = 1 and Hot sichuan = 1 then 1.000
5 1 if Cumin BBQ = 1 and Cheese corn flavor = 1 then 1.000
6 1 if BBQ flavor = 1 and Hot sichuan = 1 then 1.000
5 1 if BBQ flavor = 1 and Cheese corn flavor = 1 then 1.000
5 1 if Sauced beef flavor = 1 and Hot sichuan = 1 then 1.000
10 1 if Hot sichuan = 1 and Cheese corn flavor = 1 then 1.000
6 1 if Pork steak = 1 and Chives flavor = 1 then 1.000
4 1 if Pork steak = 1 and Chicken flavor = 1 then 1.000
15 0.933 if Pork steak = 1 and Cheese corn flavor = 1 then 1.000
14 0.929 if Chives flavor = 1 and Sauced beef flavor = 1 then 1.000
14 0.927 if Chicken flavor = 1 and Cheese corn flavor = 1 then 1.000
13 0.923 if Crab flavor = 1 and Chives flavor = 1 then 1.000
13 0.923 if Crab flavor = 1 and Chicken flavor = 1 then 1.000
13 0.923 if Yolk = 1 and Chives flavor = 1 then 1.000
13 0.923 if spices salt = 1 and Chives flavor = 1 then 1.000
13 0.923 if Chives flavor = 1 and Cumin BBQ = 1 then 1.000
13 0.923 if Chives flavor = 1 and Curry beef = 1 then 1.000
13 0.923 if Chives flavor = 1 and Pepper beef steak = 1 then 1.000
13 0.923 if Chicken flavor = 1 and Cumin BBQ = 1 then 1.000
13 0.923 if Chicken flavor = 1 and Tomato flavor = 1 then 1.000
12 0.917 if Pork steak = 1 and BBQ flavor = 1 then 1.000
12 0.917 if Pork steak = 1 and Pepper beef steak = 1 then 1.000
12 0.917 if Pork steak = 1 and Sauced beef flavor = 1 then 1.000
153
12 0.917 if Crab flavor = 1 and Cumin BBQ = 1 then 1.000
12 0.917 if Crab flavor = 1 and BBQ flavor = 1 then 1.000
12 0.917 if Chicken flavor = 1 and Sauced beef flavor = 1 then 1.000
12 0.917 if Chicken flavor = 1 and Hot sichuan = 1 then 1.000
12 0.917 if Pork steak = 1 and Yolk = 1 then 1.000
12 0.917 if Pork steak = 1 and Cumin BBQ = 1 then 1.000
12 0.917 if Pork steak = 1 and Tomato flavor = 1 then 1.000
11 0.909 if Pork steak = 1 and Hot sichuan = 1 then 1.000
11 0.909 if Crab flavor = 1 and Yolk = 1 then 1.000
11 0.909 if Chicken flavor = 1 and Pepper beef steak = 1 then 1.000
11 0.909 if Pork steak = 1 and Crab flavor = 1 then 1.000
Crab Flavor Rule Set
1.000 = Crab Flavor
ID Probability Rule
4 1 if Pork steak = 1 and Tomato flavor = 1 then 1.000
5 1 if Chives flavor = 1 and Tomato flavor = 1 then 1.000
5 1 if Chicken flavor = 1 and Tomato flavor = 1 then 1.000
5 1 if Chicken flavor = 1 and Curry beef = 1 then 1.000
14 0.929 if Tomato flavor = 1 and Sauced beef flavor = 1 then 1.000
10 0.9 if Tomato flavor = 1 and Kimchi flavor = 1 then 1.000
Chicken Flavor Rule Set
1.000 = Chicken Flavor
ID Probability Rule
12 1 if Pork steak = 1 then 1.000
4 1 if Pork steak = 1 and Pepper beef steak = 1 then 1.000
6 1 if Pork steak = 1 and Sauced beef flavor = 1 then 1.000
12 1 if Pork steak = 1 and Hot sichuan = 1 then 1.000
10 1 if Pork steak = 1 and Cheese corn flavor = 1 then 1.000
11 1 if Pork steak = 1 and Kimchi flavor = 1 then 1.000
5 1 if Crab flavor = 1 and Chives flavor = 1 then 1.000
5 1 if Crab flavor = 1 and Cumin BBQ = 1 then 1.000
12 1 if Yolk = 1 and Chives flavor = 1 then 1.000
11 1 if Yolk = 1 and Hot sichuan = 1 then 1.000
13 1 if Chives flavor = 1 and Cumin BBQ = 1 then 1.000
5 1 if Chives flavor = 1 and Tomato flavor = 1 then 1.000
13 1 if Chives flavor = 1 and BBQ flavor = 1 then 1.000
12 1 if Cumin BBQ = 1 and Hot sichuan = 1 then 1.000
12 1 if Cumin BBQ = 1 and Kimchi flavor = 1 then 1.000
4 1 if Pork steak = 1 and Crab flavor = 1 then 1.000
11 1 if Pork steak = 1 and Yolk = 1 then 1.000
12 1 if Pork steak = 1 and Chives flavor = 1 then 1.000
154
12 1 if Pork steak = 1 and Cumin BBQ = 1 then 1.000
4 1 if Pork steak = 1 and Tomato flavor = 1 then 1.000
12 1 if Pork steak = 1 and BBQ flavor = 1 then 1.000
14 0.929 if Chives flavor = 1 then 1.000
14 0.929 if Cumin BBQ = 1 and BBQ flavor = 1 then 1.000
14 0.929 if Cumin BBQ = 1 then 1.000
13 0.923 if Yolk = 1 and Cumin BBQ = 1 then 1.000
13 0.923 if Yolk = 1 and BBQ flavor = 1 then 1.000
13 0.923 if Chives flavor = 1 and Hot sichuan = 1 then 1.000
13 0.923 if Chives flavor = 1 and Kimchi flavor = 1 then 1.000
13 0.923 if BBQ flavor = 1 and Hot sichuan = 1 then 1.000
13 0.923 if BBQ flavor = 1 and Kimchi flavor = 1 then 1.000
12 0.917 if Yolk = 1 and Kimchi flavor = 1 then 1.000
12 0.917 if Chives flavor = 1 and Cheese corn flavor = 1 then 1.000
12 0.917 if Cumin BBQ = 1 and Cheese corn flavor = 1 then 1.000
11 0.909 if Yolk = 1 and Cheese corn flavor = 1 then 1.000
Pepper Beef Steak Flavor Rule Set
1.000 = Pepper Beef Steak Flavor
ID Probability Rule
16 1 if spices salt = 1 and Curry beef = 1 then 1.000
5 1 if Yolk = 1 and Curry beef = 1 then 1.000
11 1 if Crab flavor = 1 and Curry beef = 1 then 1.000
11 1 if Curry beef = 1 and Kimchi flavor = 1 then 1.000
11 1 if Curry beef = 1 and Cheese corn flavor = 1 then 1.000
9 1 if Curry beef = 1 and Hot sichuan = 1 then 1.000
13 1 if Curry beef = 1 and Sauced beef flavor = 1 then 1.000
6 1 if Curry beef = 1 and BBQ flavor = 1 then 1.000
15 1 if Tomato flavor = 1 and Curry beef = 1 then 1.000
5 1 if Cumin BBQ = 1 and Curry beef = 1 then 1.000
5 1 if Chicken flavor = 1 and Curry beef = 1 then 1.000
5 1 if Chives flavor = 1 and Curry beef = 1 then 1.000
19 1 if Curry beef = 1 then 1.000
14 0.929 if spices salt = 1 and Tomato flavor = 1 then 1.000
12 0.927 if spices salt = 1 and Sauced beef flavor = 1 then 1.000
11 0.909 if spices salt = 1 and Cheese corn flavor = 1 then 1.000
11 0.909 if spices salt = 1 and Kimchi flavor = 1 then 1.000
10 0.9 if Crab flavor = 1 and Kimchi flavor = 1 then 1.000
10 0.9 if Crab flavor = 1 and spices salt = 1 then 1.000
10 0.9 if Tomato flavor = 1 and Kimchi flavor = 1 then 1.000
Pork Steak Flavor Rule Set
1.000 = Pork Steak Flavor
155
ID Probability Rule
12 1 if Cumin BBQ = 1 and Hot sichuan = 1 then 1.000
11 1 if Yolk = 1 and Hot sichuan = 1 then 1.000
13 0.923 if Chicken flavor = 1 and Hot sichuan = 1 then 1.000
13 0.923 if BBQ flavor = 1 and Hot sichuan = 1 then 1.000
13 0.923 if Chives flavor = 1 and Chicken flavor = 1 then 1.000
13 0.923 if Chives flavor = 1 and Cumin BBQ = 1 then 1.000
13 0.923 if Chives flavor = 1 and BBQ flavor = 1 then 1.000
13 0.923 if Chives flavor = 1 and Hot sichuan = 1 then 1.000
13 0.923 if Chicken flavor = 1 and Cumin BBQ = 1 then 1.000
13 0.923 if Chicken flavor = 1 and BBQ flavor = 1 then 1.000
12 0.917 if Yolk = 1 and Chives flavor = 1 then 1.000
12 0.917 if Cumin BBQ = 1 and Kimchi flavor = 1 then 1.000
12 0.917 if Yolk = 1 and Chicken flavor = 1 then 1.000
Tomato Flavor Rule Set
1.000 = Tomato Flavor
ID Probability Rule
1 1 if Pork steak = 1 and Crab flavor = 1 then 1.000
1 1 if Yolk = 1 and Curry beef = 1 then 1.000
1 1 if Cumin BBQ = 1 and Curry beef = 1 then 1.000
1 1 if Curry beef = 1 and BBQ flavor = 1 then 1.000
1 1 if Crab flavor = 1 and Yolk = 1 then 1.000
1 1 if Crab flavor = 1 and Chives flavor = 1 then 1.000
1 1 if Crab flavor = 1 and Cumin BBQ = 1 then 1.000
1 1 if Crab flavor = 1 and BBQ flavor = 1 then 1.000
1 0.929 if Crab flavor = 1 and Sauced beef flavor = 1 then 1.000
1 0.909 if Crab flavor = 1 and Curry beef = 1 then 1.000
1 0.9 if Crab flavor = 1 and spices salt = 1 then 1.000
1 0.9 if Crab flavor = 1 and Kimchi flavor = 1 then 1.000
Chives Flavor Rule Set
1.000 = Chives Flavor
ID Probability Rule
12 1 if Pork steak = 1 then 1.000
4 1 if Pork steak = 1 and Pepper beef steak = 1 then 1.000
16 1 if Pork steak = 1 and Sauced beef flavor = 1 then 1.000
12 1 if Pork steak = 1 and Hot sichuan = 1 then 1.000
10 1 if Pork steak = 1 and Cheese corn flavor = 1 then 1.000
11 1 if Pork steak = 1 and Kimchi flavor = 1 then 1.000
5 1 if Crab flavor = 1 and Cumin BBQ = 1 then 1.000
12 1 if Yolk = 1 and Chicken flavor = 1 then 1.000
11 1 if Yolk = 1 and Hot sichuan = 1 then 1.000
156
14 1 if Chicken flavor = 1 and Cumin BBQ = 1 then 1.000
5 1 if Chicken flavor = 1 and Tomato flavor = 1 then 1.000
13 1 if Chicken flavor = 1 and BBQ flavor = 1 then 1.000
12 1 if Cumin BBQ = 1 and Hot sichuan = 1 then 1.000
12 1 if Cumin BBQ = 1 and Kimchi flavor = 1 then 1.000
4 1 if Pork steak = 1 and Crab flavor = 1 then 1.000
11 1 if Pork steak = 1 and Yolk = 1 then 1.000
12 1 if Pork steak = 1 and Chicken flavor = 1 then 1.000
12 1 if Pork steak = 1 and Cumin BBQ = 1 then 1.000
4 1 if Pork steak = 1 and Tomato flavor = 1 then 1.000
12 1 if Pork steak = 1 and BBQ flavor = 1 then 1.000
14 0.929 if Chicken flavor = 1 then 1.000
14 0.929 if Cumin BBQ = 1 and BBQ flavor = 1 then 1.000
14 0.929 if Cumin BBQ = 1 then 1.000
13 0.923 if Yolk = 1 and Cumin BBQ = 1 then 1.000
13 0.923 if Yolk = 1 and BBQ flavor = 1 then 1.000
13 0.923 if Chicken flavor = 1 and Hot sichuan = 1 then 1.000
13 0.923 if Chicken flavor = 1 and Kimchi flavor = 1 then 1.000
13 0.923 if BBQ flavor = 1 and Hot sichuan = 1 then 1.000
13 0.923 if BBQ flavor = 1 and Kimchi flavor = 1 then 1.000
12 0.917 if Yolk = 1 and Kimchi flavor = 1 then 1.000
12 0.917 if Chicken flavor = 1 and Cheese corn flavor = 1 then 1.000
12 0.917 if Cumin BBQ = 1 and Cheese corn flavor = 1 then 1.000
11 0.909 if Yolk = 1 and Cheese corn flavor = 1 then 1.000
Sauced Beef Flavor Rule Set
1.000 = Sauced Beef Flavor
ID Probability Rule
5 1 if Crab flavor = 1 and Cumin BBQ = 1 then 1.000
6 1 if Crab flavor = 1 and Chicken flavor = 1 then 1.000
5 1 if Crab flavor = 1 and Chives flavor = 1 then 1.000
10 1 if Crab flavor = 1 and spices salt = 1 then 1.000
5 1 if Crab flavor = 1 and Yolk = 1 then 1.000
7 1 if BBQ flavor = 1 and Pepper beef steak = 1 then 1.000
4 1 if Pork steak = 1 and Pepper beef steak = 1 then 1.000
6 1 if Curry beef = 1 and BBQ flavor = 1 then 1.000
9 1 if Tomato flavor = 1 and Cheese corn flavor = 1 then 1.000
7 1 if Tomato flavor = 1 and BBQ flavor = 1 then 1.000
6 1 if Cumin BBQ = 1 and Pepper beef steak = 1 then 1.000
5 1 if Cumin BBQ = 1 and Curry beef = 1 then 1.000
6 1 if Cumin BBQ = 1 and Tomato flavor = 1 then 1.000
6 1 if Chicken flavor = 1 and Pepper beef steak = 1 then 1.000
157
5 1 if Chicken flavor = 1 and Curry beef = 1 then 1.000
5 1 if Chicken flavor = 1 and Tomato flavor = 1 then 1.000
4 1 if Pork steak = 1 and Tomato flavor = 1 then 1.000
6 1 if Chives flavor = 1 and Pepper beef steak = 1 then 1.000
5 1 if Chives flavor = 1 and Curry beef = 1 then 1.000
5 1 if Chives flavor = 1 and Tomato flavor = 1 then 1.000
6 1 if Yolk = 1 and Pepper beef steak = 1 then 1.000
5 1 if Yolk = 1 and Curry beef = 1 then 1.000
6 1 if Yolk = 1 and Tomato flavor = 1 then 1.000
10 1 if Crab flavor = 1 and Kimchi flavor = 1 then 1.000
9 1 if Crab flavor = 1 and Cheese corn flavor = 1 then 1.000
6 1 if Crab flavor = 1 and BBQ flavor = 1 then 1.000
4 1 if Pork steak = 1 and Crab flavor = 1 then 1.000
14 0.929 if Crab flavor = 1 and Tomato flavor = 1 then 1.000
12 0.917 if Pepper beef steak = 1 and Kimchi flavor = 1 then 1.000
12 0.917 if Pepper beef steak = 1 and Cheese corn flavor = 1 then 1.000
11 0.909 if Curry beef = 1 and Kimchi flavor = 1 then 1.000
11 0.909 if Curry beef = 1 and Cheese corn flavor = 1 then 1.000
11 0.909 if Crab flavor = 1 and Curry beef = 1 then 1.000
10 0.9 if Tomato flavor = 1 and Kimchi flavor = 1 then 1.000
BBQ Flavor Rule Set
1.000 = BBQ Flavor
ID Probability Rule
12 1 if Pork steak = 1 and Hot sichuan = 1 then 1.000
10 1 if Pork steak = 1 and Cheese corn flavor = 1 then 1.000
11 1 if Pork steak = 1 and Kimchi flavor = 1 then 1.000
5 1 if Crab flavor = 1 and Chives flavor = 1 then 1.000
5 1 if Crab flavor = 1 and Cumin BBQ = 1 then 1.000
12 1 if Yolk = 1 and Chives flavor = 1 then 1.000
12 1 if Yolk = 1 and Chicken flavor = 1 then 1.000
13 1 if Yolk = 1 and Cumin BBQ = 1 then 1.000
11 1 if Yolk = 1 and Hot sichuan = 1 then 1.000
11 1 if Yolk = 1 and Cheese corn flavor = 1 then 1.000
5 1 if spices salt = 1 and Cumin BBQ = 1 then 1.000
13 1 if Chives flavor = 1 and Chicken flavor = 1 then 1.000
13 1 if Chives flavor = 1 and Cumin BBQ = 1 then 1.000
5 1 if Chives flavor = 1 and Tomato flavor = 1 then 1.000
13 1 if Chicken flavor = 1 and Cumin BBQ = 1 then 1.000
5 1 if Chicken flavor = 1 and Tomato flavor = 1 then 1.000
6 1 if Cumin BBQ = 1 and Tomato flavor = 1 then 1.000
5 1 if Cumin BBQ = 1 and Curry beef = 1 then 1.000
158
6 1 if Cumin BBQ = 1 and Pepper beef steak = 1 then 1.000
8 1 if Cumin BBQ = 1 and Sauced beef flavor = 1 then 1.000
12 1 if Cumin BBQ = 1 and Hot sichuan = 1 then 1.000
12 1 if Cumin BBQ = 1 and Cheese corn flavor = 1 then 1.000
12 1 if Cumin BBQ = 1 and Kimchi flavor = 1 then 1.000
14 1 if Cumin BBQ = 1 then 1.000
4 1 if Pork steak = 1 and Crab flavor = 1 then 1.000
11 1 if Pork steak = 1 and Yolk = 1 then 1.000
12 1 if Pork steak = 1 and Chives flavor = 1 then 1.000
12 1 if Pork steak = 1 and Chicken flavor = 1 then 1.000
14 0.929 if Yolk = 1 then 1.000
14 0.929 if Chives flavor = 1 then 1.000
14 0.929 if Chicken flavor = 1 then 1.000
13 0.923 if Chives flavor = 1 and Hot sichuan = 1 then 1.000
13 0.923 if Chives flavor = 1 and Kimchi flavor = 1 then 1.000
13 0.923 if Chicken flavor = 1 and Hot sichuan = 1 then 1.000
13 0.923 if Chicken flavor = 1 and Kimchi flavor = 1 then 1.000
12 0.917 if Yolk = 1 and Kimchi flavor = 1 then 1.000
12 0.917 if Chives flavor = 1 and Cheese corn flavor = 1 then 1.000
12 0.917 if Chicken flavor = 1 and Cheese corn flavor = 1 then 1.000
Cumin BBQ Flavor Rule Set
1.000 = Cumin BBQ Flavor
ID Probability Rule
12 1 if Pork steak = 1 then 1.000
4 1 if Pork steak = 1 and Tomato flavor = 1 then 1.000
12 1 if Pork steak = 1 and BBQ flavor = 1 then 1.000
4 1 if Pork steak = 1 and Pepper beef steak = 1 then 1.000
6 1 if Pork steak = 1 and Sauced beef flavor = 1 then 1.000
12 1 if Pork steak = 1 and Hot sichuan = 1 then 1.000
10 1 if Pork steak = 1 and Cheese corn flavor = 1 then 1.000
11 1 if Pork steak = 1 and Kimchi flavor = 1 then 1.000
5 1 if Crab flavor = 1 and Chives flavor = 1 then 1.000
12 1 if Yolk = 1 and Chives flavor = 1 then 1.000
12 1 if Yolk = 1 and Chicken flavor = 1 then 1.000
13 1 if Yolk = 1 and BBQ flavor = 1 then 1.000
11 1 if Yolk = 1 and Hot sichuan = 1 then 1.000
11 1 if Yolk = 1 and Cheese corn flavor = 1 then 1.000
13 1 if Chives flavor = 1 and Chicken flavor = 1 then 1.000
5 1 if Chives flavor = 1 and Tomato flavor = 1 then 1.000
13 1 if Chives flavor = 1 and BBQ flavor = 1 then 1.000
5 1 if Chicken flavor = 1 and Tomato flavor = 1 then 1.000
159
13 1 if Chicken flavor = 1 and BBQ flavor = 1 then 1.000
4 1 if Pork steak = 1 and Crab flavor = 1 then 1.000
11 1 if Pork steak = 1 and Yolk = 1 then 1.000
12 1 if Pork steak = 1 and Chives flavor = 1 then 1.000
12 1 if Pork steak = 1 and Chicken flavor = 1 then 1.000
15 0.933 if BBQ flavor = 1 then 1.000
14 0.929 if Yolk = 1 then 1.000
14 0.929 if Chives flavor = 1 then 1.000
14 0.929 if Chicken flavor = 1 then 1.000
13 0.923 if Chives flavor = 1 and Hot sichuan = 1 then 1.000
13 0.923 if Chives flavor = 1 and Kimchi flavor = 1 then 1.000
13 0.923 if Chicken flavor = 1 and Hot sichuan = 1 then 1.000
13 0.923 if Chicken flavor = 1 and Kimchi flavor = 1 then 1.000
13 0.923 if BBQ flavor = 1 and Hot sichuan = 1 then 1.000
13 0.923 if BBQ flavor = 1 and Cheese corn flavor = 1 then 1.000
13 0.923 if BBQ flavor = 1 and Kimchi flavor = 1 then 1.000
12 0.917 if Yolk = 1 and Kimchi flavor = 1 then 1.000
12 0.917 if Chives flavor = 1 and Cheese corn flavor = 1 then 1.000
12 0.917 if Chicken flavor = 1 and Cheese corn flavor = 1 then 1.000
Curry Beef Flavor Rule Set
1.000 = Curry Beef Flavor
ID Probability Rule
15 1 if Tomato flavor = 1 and Pepper beef steak = 1 then 1.000
16 1 if spices salt = 1 and Pepper beef steak = 1 then 1.000
14 0.929 if Pepper beef steak = 1 and Sauced beef flavor = 1 then 1.000
14 0.929 if spices salt = 1 and Tomato flavor = 1 then 1.000
12 0.917 if Pepper beef steak = 1 and Cheese corn flavor = 1 then 1.000
12 0.917 if Pepper beef steak = 1 and Kimchi flavor = 1 then 1.000
12 0.917 if Crab flavor = 1 and Pepper beef steak = 1 then 1.000
12 0.917 if spices salt = 1 and Sauced beef flavor = 1 then 1.000
11 0.909 if spices salt = 1 and Cheese corn flavor = 1 then 1.000
11 0.909 if spices salt = 1 and Kimchi flavor = 1 then 1.000
21 0.905 if Pepper beef steak = 1 then 1.000
10 0.9 if Tomato flavor = 1 and Kimchi flavor = 1 then 1.000
10 0.9 if Crab flavor = 1 and spices salt = 1 then 1.000
10 0.9 if Crab flavor = 1 and Kimchi flavor = 1 then 1.000
Cheese Corn Flavor Rule Set
1.000 = Cheese Corn Flavor
ID Probability Rule
11 1 if Pork steak = 1 and Kimchi flavor = 1 then 1.000
12 1 if Cumin BBQ = 1 and Kimchi flavor = 1 then 1.000
160
13 1 if Chives flavor = 1 and Kimchi flavor = 1 then 1.000
13 1 if Chicken flavor = 1 and Kimchi flavor = 1 then 1.000
13 1 if BBQ flavor = 1 and Kimchi flavor = 1 then 1.000
4 1 if Pork steak = 1 and Crab flavor = 1 then 1.000
4 1 if Pork steak = 1 and Tomato flavor = 1 then 1.000
4 1 if Pork steak = 1 and Pepper beef steak = 1 then 1.000
6 1 if Pork steak = 1 and Sauced beef flavor = 1 then 1.000
5 1 if Crab flavor = 1 and Chives flavor = 1 then 1.000
6 1 if Crab flavor = 1 and Chicken flavor = 1 then 1.000
5 1 if Crab flavor = 1 and Cumin BBQ = 1 then 1.000
6 1 if Crab flavor = 1 and BBQ flavor = 1 then 1.000
5 1 if spices salt = 1 and Chives flavor = 1 then 1.000
5 1 if spices salt = 1 and Chicken flavor = 1 then 1.000
5 1 if spices salt = 1 and Cumin BBQ = 1 then 1.000
6 1 if spices salt = 1 and BBQ flavor = 1 then 1.000
5 1 if Chives flavor = 1 and Tomato flavor = 1 then 1.000
5 1 if Chives flavor = 1 and Curry beef = 1 then 1.000
6 1 if Chives flavor = 1 and Pepper beef steak = 1 then 1.000
8 1 if Chives flavor = 1 and Sauced beef flavor = 1 then 1.000
5 1 if Chicken flavor = 1 and Tomato flavor = 1 then 1.000
5 1 if Chicken flavor = 1 and Curry beef = 1 then 1.000
6 1 if Chicken flavor = 1 and Pepper beef steak = 1 then 1.000
8 1 if Chicken flavor = 1 and Sauced beef flavor = 1 then 1.000
6 1 if Cumin BBQ = 1 and Tomato flavor = 1 then 1.000
5 1 if Cumin BBQ = 1 and Curry beef = 1 then 1.000
6 1 if Cumin BBQ = 1 and Pepper beef steak = 1 then 1.000
8 0.923 if Cumin BBQ = 1 and Sauced beef flavor = 1 then 1.000
7 0.923 if Tomato flavor = 1 and BBQ flavor = 1 then 1.000
6 0.923 if Curry beef = 1 and BBQ flavor = 1 then 1.000
7 0.917 if BBQ flavor = 1 and Pepper beef steak = 1 then 1.000
9 0.909 if BBQ flavor = 1 and Sauced beef flavor = 1 then 1.000 Table 15 Scoring information for Top 10 Rules in East China Region Year 2013 2014 2015 2014 2015 2013 2015 2013 2014 2013
Month Mon May Sep Feb Jun Nov Mar Aug Dec May Tomato flavor 1 1 1 1 0 1 0 1 0 1
Crab flavor 0 1 1 0 0 1 0 0 0 1
Sauced beef 0 1 1 0 1 1 0 1 1 1 Cheese corn 0 0 1 0 1 0 1 1 1 0
BBQ flavor 0 0 1 0 1 0 1 1 0 0 Pepper beef 1 0 1 0 0 1 0 1 1 0
161
Chicken flavor 0 0 1 0 1 0 1 0 0 0 Curry beef 1 0 1 0 0 1 0 1 1 0
Cumin BBQ 0 0 1 0 1 0 1 1 0 0 spices salt 1 1 1 0 0 1 0 1 1 0
Pork steak 0 0 1 0 1 0 1 0 0 0
Yolk 0 0 1 0 1 0 1 1 0 0 Kimchi flavor 0 0 1 0 1 1 1 0 1 0
Chives flavor 0 0 1 0 1 0 1 0 1 0 Hot sichuan 0 0 1 0 1 0 1 0 1 0
Prediction 1 PBS CKF BQF
Confidence 1 0.92
9 0.92
9 0.92
9 Rule ID 1 237 225 230
Prediction 2 CBF CVF CKF
Confidence 2 0.92
9 0.92
9 0.92
9 Rule ID 2 238 227 231
Prediction 3 CF CBQ
Confidence 3 0.92
9 0.92
9 Rule ID 3 236 232
Table 16 Results for the South West China Region
Consequent Antecedent Support % Confidence % Lift
1 CKF YF 33.333 100 2.571
2 BQF YF 33.333 100 2.25
3 CBQ YF 33.333 100 2.25
4 CVF YF 33.333 100 2
5 BQF CKF 38.889 100 2.25
6 YF PSF and CF 13.889 100 3
7 CKF PSF and CF 13.889 100 2.571
8 BQF PSF and CF 13.889 100 2.25
9 CBQ PSF and CF 13.889 100 2.25
10 HSC PSF and CF 13.889 100 2
11 CVF PSF and CF 13.889 100 2
12 CKF PSF and YF 30.556 100 2.571
13 YF PSF and CKF 30.556 100 3
14 YF PSF and KF 22.222 100 3
15 YF PSF and TF 13.889 100 3
16 BQF PSF and YF 30.556 100 2.25
17 YF PSF and BQF 30.556 100 3
18 CBQ PSF and YF 30.556 100 2.25
162
19 YF PSF and CBQ 30.556 100 3
20 HSC PSF and YF 30.556 100 2
21 YF PSF and HSC 30.556 100 3
22 PSF YF and HSC 30.556 100 3
23 YF PSF and CCF 22.222 100 3
24 CVF PSF and YF 30.556 100 2
25 YF PSF and CVF 30.556 100 3
26 YF PSF and SBF 27.778 100 3
27 CKF PSF and KF 22.222 100 2.571
28 CKF PSF and TF 13.889 100 2.571
29 BQF PSF and CKF 30.556 100 2.25
30 CKF PSF and BQF 30.556 100 2.571
31 CBQ PSF and CKF 30.556 100 2.25
32 CKF PSF and CBQ 30.556 100 2.571
33 HSC PSF and CKF 30.556 100 2
34 CKF PSF and HSC 30.556 100 2.571
35 CKF PSF and CCF 22.222 100 2.571
36 CVF PSF and CKF 30.556 100 2
37 CKF PSF and CVF 30.556 100 2.571
38 CKF PSF and SBF 27.778 100 2.571
39 KF PSF and TF 13.889 100 2.4
40 BQF PSF and KF 22.222 100 2.25
41 CBQ PSF and KF 22.222 100 2.25
42 HSC PSF and KF 22.222 100 2
43 CVF PSF and KF 22.222 100 2
44 SBF PSF and KF 22.222 100 1.714
45 BQF PSF and TF 13.889 100 2.25
46 CBQ PSF and TF 13.889 100 2.25
47 HSC PSF and TF 13.889 100 2
48 CVF PSF and TF 13.889 100 2
49 SBF PSF and TF 13.889 100 1.714
50 CBQ PSF and BQF 30.556 100 2.25
51 BQF PSF and CBQ 30.556 100 2.25
52 HSC PSF and BQF 30.556 100 2
53 BQF PSF and HSC 30.556 100 2.25
54 BQF PSF and CCF 22.222 100 2.25
55 CVF PSF and BQF 30.556 100 2
56 BQF PSF and CVF 30.556 100 2.25
57 BQF PSF and SBF 27.778 100 2.25
58 HSC PSF and CBQ 30.556 100 2
59 CBQ PSF and HSC 30.556 100 2.25
163
60 CBQ PSF and CCF 22.222 100 2.25
61 CVF PSF and CBQ 30.556 100 2
62 CBQ PSF and CVF 30.556 100 2.25
63 CBQ PSF and SBF 27.778 100 2.25
64 HSC PSF and CCF 22.222 100 2
65 CVF PSF and HSC 30.556 100 2
66 HSC PSF and CVF 30.556 100 2
67 HSC PSF and SBF 27.778 100 2
68 CVF PSF and CCF 22.222 100 2
69 CVF PSF and SBF 27.778 100 2
70 CKF CF and YF 16.667 100 2.571
71 YF CF and CKF 16.667 100 3
72 BQF CF and YF 16.667 100 2.25
73 YF CF and BQF 16.667 100 3
74 CBQ CF and YF 16.667 100 2.25
75 CVF CF and YF 16.667 100 2
76 BQF CF and CKF 16.667 100 2.25
77 CKF CF and BQF 16.667 100 2.571
78 CBQ CF and CKF 16.667 100 2.25
79 CVF CF and CKF 16.667 100 2
80 CBQ CF and BQF 16.667 100 2.25
81 CVF CF and BQF 16.667 100 2
82 CVF CF and CBQ 19.444 100 2
83 CKF YF and KF 25 100 2.571
84 CKF YF and CBF 11.111 100 2.571
85 CKF YF and TF 16.667 100 2.571
86 BQF YF and CKF 33.333 100 2.25
87 CKF YF and BQF 33.333 100 2.571
88 CBQ YF and CKF 33.333 100 2.25
89 CKF YF and CBQ 33.333 100 2.571
90 CKF YF and HSC 30.556 100 2.571
91 CKF YF and CCF 25 100 2.571
92 CVF YF and CKF 33.333 100 2
93 CKF YF and CVF 33.333 100 2.571
94 CKF YF and SBF 30.556 100 2.571
95 KF YF and CBF 11.111 100 2.4
96 KF YF and TF 16.667 100 2.4
97 BQF YF and KF 25 100 2.25
98 CBQ YF and KF 25 100 2.25
99 CVF YF and KF 25 100 2
100 SBF YF and KF 25 100 1.714
164
101 TF YF and CBF 11.111 100 1.895
102 BQF YF and CBF 11.111 100 2.25
103 CBQ YF and CBF 11.111 100 2.25
104 CCF YF and CBF 11.111 100 1.895
105 CVF YF and CBF 11.111 100 2
106 SBF YF and CBF 11.111 100 1.714
107 BQF YF and TF 16.667 100 2.25
108 CBQ YF and TF 16.667 100 2.25
109 CVF YF and TF 16.667 100 2
110 SBF YF and TF 16.667 100 1.714
111 CBQ YF and BQF 33.333 100 2.25
112 BQF YF and CBQ 33.333 100 2.25
113 BQF YF and HSC 30.556 100 2.25
114 BQF YF and CCF 25 100 2.25
115 CVF YF and BQF 33.333 100 2
116 BQF YF and CVF 33.333 100 2.25
117 BQF YF and SBF 30.556 100 2.25
118 CBQ YF and HSC 30.556 100 2.25
119 CBQ YF and CCF 25 100 2.25
120 CVF YF and CBQ 33.333 100 2
121 CBQ YF and CVF 33.333 100 2.25
122 CBQ YF and SBF 30.556 100 2.25
123 CVF YF and HSC 30.556 100 2
124 CVF YF and CCF 25 100 2
125 CVF YF and SBF 30.556 100 2
126 PBS HSS and CKF 11.111 100 1.8
127 CBF HSS and CKF 11.111 100 2
128 TF HSS and CKF 11.111 100 1.895
129 BQF HSS and CKF 11.111 100 2.25
130 CCF HSS and CKF 11.111 100 1.895
131 SBF HSS and CKF 11.111 100 1.714
132 PBS HSS and KF 22.222 100 1.8
133 PBS HSS and CBF 44.444 100 1.8
134 PBS HSS and TF 36.111 100 1.8
135 PBS HSS and BQF 16.667 100 1.8
136 PBS HSS and CBQ 16.667 100 1.8
137 PBS HSS and HSC 22.222 100 1.8
138 PBS HSS and CCF 33.333 100 1.8
139 PBS HSS and CVF 22.222 100 1.8
140 CBF HSS and KF 22.222 100 2
141 CCF HSS and KF 22.222 100 1.895
165
142 CBF HSS and BQF 16.667 100 2
143 CBF HSS and CBQ 16.667 100 2
144 CBF HSS and HSC 22.222 100 2
145 CBF HSS and CCF 33.333 100 2
146 CBF HSS and CVF 22.222 100 2
147 CCF HSS and BQF 16.667 100 1.895
148 SBF HSS and BQF 16.667 100 1.714
149 CCF HSS and CVF 22.222 100 1.895
150 CBF CKF and PBS 13.889 100 2
151 TF CKF and PBS 13.889 100 1.895
152 BQF CKF and PBS 13.889 100 2.25
153 CCF CKF and PBS 13.889 100 1.895
154 SBF CKF and PBS 13.889 100 1.714
155 BQF CKF and KF 27.778 100 2.25
156 CKF KF and BQF 27.778 100 2.571
157 CBQ CKF and KF 27.778 100 2.25
158 CVF CKF and KF 27.778 100 2
159 SBF CKF and KF 27.778 100 1.714
160 TF CKF and CBF 16.667 100 1.895
161 BQF CKF and CBF 16.667 100 2.25
162 CCF CKF and CBF 16.667 100 1.895
163 SBF CKF and CBF 16.667 100 1.714
164 BQF CKF and TF 22.222 100 2.25
165 SBF CKF and TF 22.222 100 1.714
166 BQF CKF and CBQ 36.111 100 2.25
167 BQF CKF and HSC 33.333 100 2.25
168 BQF CKF and CCF 30.556 100 2.25
169 BQF CKF and CVF 36.111 100 2.25
170 BQF CKF and SBF 36.111 100 2.25
171 CBQ CKF and HSC 33.333 100 2.25
172 CVF CKF and CBQ 36.111 100 2
173 CBQ CKF and CVF 36.111 100 2.25
174 CVF CKF and HSC 33.333 100 2
175 CBF PBS and KF 25 100 2
176 CCF PBS and KF 25 100 1.895
177 CBF PBS and BQF 19.444 100 2
178 CBF PBS and CBQ 19.444 100 2
179 CBF PBS and HSC 25 100 2
180 CBF PBS and CCF 36.111 100 2
181 CBF PBS and CVF 25 100 2
182 CBF PBS and SBF 33.333 100 2
166
183 CCF PBS and BQF 19.444 100 1.895
184 SBF PBS and BQF 19.444 100 1.714
185 CCF PBS and CVF 25 100 1.895
186 CCF KF and CBF 27.778 100 1.895
187 CBQ KF and BQF 27.778 100 2.25
188 CVF KF and BQF 27.778 100 2
189 SBF KF and BQF 27.778 100 1.714
190 CVF KF and CBQ 30.556 100 2
191 SBF KF and CBQ 30.556 100 1.714
192 CBF TF and CCF 30.556 100 2
193 CCF CBF and BQF 22.222 100 1.895
194 SBF CBF and BQF 22.222 100 1.714
195 CCF CBF and CVF 27.778 100 1.895
196 SBF TF and BQF 25 100 1.714
197 CVF BQF and CBQ 38.889 100 2
198 CBQ BQF and CVF 38.889 100 2.25
199 CVF CBQ and HSC 38.889 100 2
200 CBQ HSC and CVF 38.889 100 2.25
201 CVF CBQ and CCF 33.333 100 2
202 CVF CBQ and SBF 38.889 100 2
203 PBS CBF 50 94.444 1.7
204 CBF HSS and PBS 47.222 94.118 1.882
205 HSS PBS and CBF 47.222 94.118 1.783
206 SBF BQF 44.444 93.75 1.607
207 CVF CBQ 44.444 93.75 1.875
208 BQF CBQ and CVF 41.667 93.333 2.1
209 HSC CBQ and CVF 41.667 93.333 1.867
210 SBF CBQ and CVF 41.667 93.333 1.6
211 CBQ CKF 38.889 92.857 2.089
212 CVF CKF 38.889 92.857 1.857
213 SBF CKF 38.889 92.857 1.592
214 CBQ CKF and BQF 38.889 92.857 2.089
215 CKF BQF and CBQ 38.889 92.857 2.388
216 CVF CKF and BQF 38.889 92.857 1.857
217 CKF BQF and CVF 38.889 92.857 2.388
218 SBF CKF and BQF 38.889 92.857 1.592
219 PBS CBF and TF 38.889 92.857 1.671
220 PBS CBF and CCF 38.889 92.857 1.671
221 HSC BQF and CBQ 38.889 92.857 1.857
222 CBQ BQF and HSC 38.889 92.857 2.089
223 BQF CBQ and HSC 38.889 92.857 2.089
167
224 SBF BQF and CBQ 38.889 92.857 1.592
225 BQF CBQ and SBF 38.889 92.857 2.089
226 CVF BQF and HSC 38.889 92.857 1.857
227 HSC BQF and CVF 38.889 92.857 1.857
228 BQF HSC and CVF 38.889 92.857 2.089
229 SBF BQF and HSC 38.889 92.857 1.592
230 SBF BQF and CVF 38.889 92.857 1.592
231 SBF CBQ and HSC 38.889 92.857 1.592
232 HSC CBQ and SBF 38.889 92.857 1.857
233 SBF HSC and CVF 38.889 92.857 1.592
234 YF CKF and CBQ 36.111 92.308 2.769
235 YF CKF and CVF 36.111 92.308 2.769
236 HSS PBS and CCF 36.111 92.308 1.749
237 CBF HSS and TF 36.111 92.308 1.846
238 HSC CKF and CBQ 36.111 92.308 1.846
239 SBF CKF and CBQ 36.111 92.308 1.582
240 CBQ CKF and SBF 36.111 92.308 2.077
241 HSC CKF and CVF 36.111 92.308 1.846
242 SBF CKF and CVF 36.111 92.308 1.582
243 CVF CKF and SBF 36.111 92.308 1.846
244 PBS CBF and SBF 36.111 92.308 1.662
245 SBF KF and CVF 36.111 92.308 1.582
246 CVF KF and SBF 36.111 92.308 1.846
247 CCF CBF and SBF 36.111 92.308 1.749
248 SBF BQF and CCF 36.111 92.308 1.582
249 YF PSF 33.333 91.667 2.75
250 PSF YF 33.333 91.667 2.75
251 CKF PSF 33.333 91.667 2.357
252 BQF PSF 33.333 91.667 2.062
253 CBQ PSF 33.333 91.667 2.062
254 HSC PSF 33.333 91.667 1.833
255 CVF PSF 33.333 91.667 1.833
256 HSC YF 33.333 91.667 1.833
257 SBF YF 33.333 91.667 1.571
258 PSF YF and CKF 33.333 91.667 2.75
259 PSF YF and BQF 33.333 91.667 2.75
260 PSF YF and CBQ 33.333 91.667 2.75
261 PSF YF and CVF 33.333 91.667 2.75
262 PSF CKF and HSC 33.333 91.667 2.75
263 HSC YF and CKF 33.333 91.667 1.833
264 YF CKF and HSC 33.333 91.667 2.75
168
265 SBF YF and CKF 33.333 91.667 1.571
266 HSC YF and BQF 33.333 91.667 1.833
267 SBF YF and BQF 33.333 91.667 1.571
268 HSC YF and CBQ 33.333 91.667 1.833
269 SBF YF and CBQ 33.333 91.667 1.571
270 HSC YF and CVF 33.333 91.667 1.833
271 SBF YF and CVF 33.333 91.667 1.571
272 PBS HSS and SBF 33.333 91.667 1.65
273 HSS PBS and SBF 33.333 91.667 1.737
274 CBF HSS and SBF 33.333 91.667 1.833
275 SBF CKF and HSC 33.333 91.667 1.571
276 CCF PBS and SBF 33.333 91.667 1.737
277 SBF KF and HSC 33.333 91.667 1.571
278 BQF CBQ and CCF 33.333 91.667 2.062
279 HSC CBQ and CCF 33.333 91.667 1.833
280 SBF CBQ and CCF 33.333 91.667 1.571
281 SBF PSF and YF 30.556 90.909 1.558
282 PSF YF and SBF 30.556 90.909 2.727
283 SBF PSF and CKF 30.556 90.909 1.558
284 SBF PSF and BQF 30.556 90.909 1.558
285 SBF PSF and CBQ 30.556 90.909 1.558
286 SBF PSF and HSC 30.556 90.909 1.558
287 SBF PSF and CVF 30.556 90.909 1.558
288 SBF YF and HSC 30.556 90.909 1.558
289 HSC YF and SBF 30.556 90.909 1.818
290 CKF KF and CBQ 30.556 90.909 2.338
291 CBQ CKF and CCF 30.556 90.909 2.045
292 CVF CKF and CCF 30.556 90.909 1.818
293 SBF CKF and CCF 30.556 90.909 1.558
294 PBS TF and CCF 30.556 90.909 1.636
295 BQF KF and CBQ 30.556 90.909 2.045
296 HSC KF and CBQ 30.556 90.909 1.818
297 SBF TF and CVF 30.556 90.909 1.558
298 CVF TF and SBF 30.556 90.909 1.818
299 YF CKF and KF 27.778 90 2.7
300 YF KF and BQF 27.778 90 2.7
301 HSC CKF and KF 27.778 90 1.8
302 PBS KF and CBF 27.778 90 1.62
303 PBS CBF and HSC 27.778 90 1.62
304 PBS CBF and CVF 27.778 90 1.62
305 CVF KF and TF 27.778 90 1.8
169
306 HSC KF and BQF 27.778 90 1.8
307 TF CBF and CVF 27.778 90 1.705
308 CCF CBF and HSC 27.778 90 1.705
309 SBF CBF and CVF 27.778 90 1.543 Table 17 Scoring for All Rule Sets (South West China Region)
Chives Flavor Rule Set
1.000 = Chives Flavor
ID Probability Rule
14 1 if Cumin BBQ = 1 and Hot sichuan = 1 then 1.000
14 1 if Cumin BBQ = 1 and Sauced beef flavor = 1 then 1.000
13 1 if Chicken flavor = 1 and Cumin BBQ = 1 then 1.000
12 1 if Yolk = 1 and Chicken flavor = 1 then 1.000
12 1 if Yolk = 1 then 1.000
12 1 if Yolk = 1 and BBQ flavor = 1 then 1.000
12 1 if Yolk = 1 and Cumin BBQ = 1 then 1.000
12 1 if Chicken flavor = 1 and Hot sichuan = 1 then 1.000
12 1 if Cumin BBQ = 1 and Cheese corn flavor = 1 then 1.000
11 1 if Pork steak = 1 and BBQ flavor = 1 then 1.000
11 1 if Pork steak = 1 and Cumin BBQ = 1 then 1.000
11 1 if Pork steak = 1 and Hot sichuan = 1 then 1.000
11 1 if Yolk = 1 and Hot sichuan = 1 then 1.000
11 1 if Yolk = 1 and Sauced beef flavor = 1 then 1.000
11 1 if Kimchi flavor = 1 and Cumin BBQ = 1 then 1.000
11 1 if Pork steak = 1 and Yolk = 1 then 1.000
11 1 if Pork steak = 1 and Chicken flavor = 1 then 1.000
10 1 if Pork steak = 1 and Sauced beef flavor = 1 then 1.000
10 1 if Chicken flavor = 1 and Kimchi flavor = 1 then 1.000
10 1 if Kimchi flavor = 1 and BBQ flavor = 1 then 1.000
9 1 if Yolk = 1 and Kimchi flavor = 1 then 1.000
9 1 if Yolk = 1 and Cheese corn flavor = 1 then 1.000
8 1 if Pork steak = 1 and Cheese corn flavor = 1 then 1.000
8 1 if Pork steak = 1 and Kimchi flavor = 1 then 1.000
7 1 if Crab flavor = 1 and Cumin BBQ = 1 then 1.000
6 1 if Crab flavor = 1 and Yolk = 1 then 1.000
6 1 if Crab flavor = 1 and Chicken flavor = 1 then 1.000
6 1 if Crab flavor = 1 and BBQ flavor = 1 then 1.000
6 1 if Yolk = 1 and Tomato flavor = 1 then 1.000
5 1 if Pork steak = 1 and Crab flavor = 1 then 1.000
5 1 if Pork steak = 1 and Tomato flavor = 1 then 1.000
16 0.938 if Cumin BBQ = 1 then 1.000
170
14 0.929 if Chicken flavor = 1 and BBQ flavor = 1 then 1.000
14 0.929 if Chicken flavor = 1 then 1.000
14 0.929 if BBQ flavor = 1 and Hot sichuan = 1 then 1.000
13 0.923 if Chicken flavor = 1 and Sauced beef flavor = 1 then 1.000
13 0.923 if Kimchi flavor = 1 and Sauced beef flavor = 1 then 1.000
12 0.917 if Pork steak = 1 then 1.000
11 0.909 if Chicken flavor = 1 and Cheese corn flavor = 1 then 1.000
11 0.909 if Tomato flavor = 1 and Sauced beef flavor = 1 then 1.000
10 0.9 if Kimchi flavor = 1 and Tomato flavor = 1 then 1.000
Chicken Flavor Rule Set
1.000 = Chicken Flavor
ID Probability Rule
8 1 if Pork steak = 1 and Cheese corn flavor = 1 then 1.000
11 1 if Pork steak = 1 and Chives flavor = 1 then 1.000
10 1 if Pork steak = 1 and Sauced beef flavor = 1 then 1.000
6 1 if Crab flavor = 1 and Yolk = 1 then 1.000
6 1 if Crab flavor = 1 and BBQ flavor = 1 then 1.000
9 1 if Yolk = 1 and Kimchi flavor = 1 then 1.000
4 1 if Yolk = 1 and Curry beef = 1 then 1.000
6 1 if Yolk = 1 and Tomato flavor = 1 then 1.000
12 1 if Yolk = 1 and BBQ flavor = 1 then 1.000
12 1 if Yolk = 1 and Cumin BBQ = 1 then 1.000
12 1 if Yolk = 1 then 1.000
11 1 if Yolk = 1 and Hot sichuan = 1 then 1.000
9 1 if Yolk = 1 and Cheese corn flavor = 1 then 1.000
12 1 if Yolk = 1 and Chives flavor = 1 then 1.000
11 1 if Yolk = 1 and Sauced beef flavor = 1 then 1.000
10 1 if Kimchi flavor = 1 and BBQ flavor = 1 then 1.000
5 1 if Pork steak = 1 and Crab flavor = 1 then 1.000
11 1 if Pork steak = 1 and Yolk = 1 then 1.000
8 1 if Pork steak = 1 and Kimchi flavor = 1 then 1.000
5 1 if Pork steak = 1 and Tomato flavor = 1 then 1.000
11 1 if Pork steak = 1 and BBQ flavor = 1 then 1.000
11 1 if Pork steak = 1 and Cumin BBQ = 1 then 1.000
11 1 if Pork steak = 1 and Hot sichuan = 1 then 1.000
14 0.929 if BBQ flavor = 1 and Cumin BBQ = 1 then 1.000
14 0.929 if BBQ flavor = 1 and Chives flavor = 1 then 1.000
12 0.917 if Pork steak = 1 then 1.000
11 0.909 if Kimchi flavor = 1 and Cumin BBQ = 1 then 1.000
Kimchi Flavor Rule Set
1.000 = Kimchi Flavor
171
ID Probability Rule
4 1 if Yolk = 1 and Curry beef = 1 then 1.000
5 1 if Pork steak = 1 and Tomato flavor = 1 then 1.000
6 1 if Yolk = 1 and Tomato flavor = 1 then 1.000
Tomato Flavor Rule Set
1.000 = Tomato Flavor
ID Probability Rule
6 1 if Chicken flavor = 1 and Curry beef = 1 then 1.000
5 1 if Chicken flavor = 1 and Pepper beef steak = 1 then 1.000
4 1 if Yolk = 1 and Curry beef = 1 then 1.000
4 1 if spices salt = 1 and Chicken flavor = 1 then 1.000
10 0.9 if Curry beef = 1 and Chives flavor = 1 then 1.000
Sauced Beef Flavor Rule Set
1.000 = Sauced Beef Flavor
ID Probability Rule
9 1 if Yolk = 1 and Kimchi flavor = 1 then 1.000
4 1 if Yolk = 1 and Curry beef = 1 then 1.000
6 1 if Yolk = 1 and Tomato flavor = 1 then 1.000
4 1 if spices salt = 1 and Chicken flavor = 1 then 1.000
6 1 if spices salt = 1 and BBQ flavor = 1 then 1.000
5 1 if Chicken flavor = 1 and Pepper beef steak = 1 then 1.000
10 1 if Chicken flavor = 1 and Kimchi flavor = 1 then 1.000
6 1 if Chicken flavor = 1 and Curry beef = 1 then 1.000
8 1 if Chicken flavor = 1 and Tomato flavor = 1 then 1.000
7 1 if Pepper beef steak = 1 and BBQ flavor = 1 then 1.000
10 1 if Kimchi flavor = 1 and BBQ flavor = 1 then 1.000
11 1 if Kimchi flavor = 1 and Cumin BBQ = 1 then 1.000
8 1 if Curry beef = 1 and BBQ flavor = 1 then 1.000
9 1 if Tomato flavor = 1 and BBQ flavor = 1 then 1.000
8 1 if Pork steak = 1 and Kimchi flavor = 1 then 1.000
5 1 if Pork steak = 1 and Tomato flavor = 1 then 1.000
16 0.938 if BBQ flavor = 1 then 1.000
15 0.933 if Cumin BBQ = 1 and Chives flavor = 1 then 1.000
14 0.929 if Chicken flavor = 1 then 1.000
14 0.929 if Chicken flavor = 1 and BBQ flavor = 1 then 1.000
14 0.929 if BBQ flavor = 1 and Cumin BBQ = 1 then 1.000
14 0.929 if BBQ flavor = 1 and Hot sichuan = 1 then 1.000
14 0.929 if BBQ flavor = 1 and Chives flavor = 1 then 1.000
14 0.929 if Cumin BBQ = 1 and Hot sichuan = 1 then 1.000
14 0.929 if Hot sichuan = 1 and Chives flavor = 1 then 1.000
13 0.923 if Chicken flavor = 1 and Cumin BBQ = 1 then 1.000
172
13 0.923 if Chicken flavor = 1 and Chives flavor = 1 then 1.000
13 0.923 if Kimchi flavor = 1 and Chives flavor = 1 then 1.000
13 0.923 if BBQ flavor = 1 and Cheese corn flavor = 1 then 1.000
12 0.917 if Yolk = 1 then 1.000
12 0.917 if Yolk = 1 and Chicken flavor = 1 then 1.000
12 0.917 if Yolk = 1 and BBQ flavor = 1 then 1.000
12 0.917 if Yolk = 1 and Cumin BBQ = 1 then 1.000
12 0.917 if Yolk = 1 and Chives flavor = 1 then 1.000
12 0.917 if Chicken flavor = 1 and Hot sichuan = 1 then 1.000
12 0.917 if Kimchi flavor = 1 and Hot sichuan = 1 then 1.000
12 0.917 if Cumin BBQ = 1 and Cheese corn flavor = 1 then 1.000
11 0.909 if Pork steak = 1 and Hot sichuan = 1 then 1.000
11 0.909 if Pork steak = 1 and Chives flavor = 1 then 1.000
11 0.909 if Yolk = 1 and Hot sichuan = 1 then 1.000
11 0.909 if Chicken flavor = 1 and Cheese corn flavor = 1 then 1.000
11 0.909 if Tomato flavor = 1 and Chives flavor = 1 then 1.000
11 0.909 if Pork steak = 1 and Yolk = 1 then 1.000
11 0.909 if Pork steak = 1 and Chicken flavor = 1 then 1.000
11 0.909 if Pork steak = 1 and BBQ flavor = 1 then 1.000
11 0.909 if Pork steak = 1 and Cumin BBQ = 1 then 1.000
10 0.9 if Curry beef = 1 and Chives flavor = 1 then 1.000
Sauced Beef Flavor Rule Set
1.000 = Sauced Beef Flavor
ID Probability Rule
11 1 if Yolk = 1 and Hot sichuan = 1 then 1.000
11 0.909 if Yolk = 1 and Sauced beef flavor = 1 then 1.000
12 0.917 if Yolk = 1 then 1.000
12 0.917 if Yolk = 1 and Chicken flavor = 1 then 1.000
12 0.917 if Yolk = 1 and BBQ flavor = 1 then 1.000
12 0.917 if Yolk = 1 and Cumin BBQ = 1 then 1.000
12 0.917 if Yolk = 1 and Chives flavor = 1 then 1.000
12 0.917 if Chicken flavor = 1 and Hot sichuan = 1 then 1.000
Pepper Beef Steak Flavor Rule Set
1.000 = Pepper Beef Steak Flavor
ID Probability Rule
8 1 if spices salt = 1 and Chives flavor = 1 then 1.000
4 1 if spices salt = 1 and Chicken flavor = 1 then 1.000
8 1 if spices salt = 1 and Kimchi flavor = 1 then 1.000
16 1 if spices salt = 1 and Curry beef = 1 then 1.000
13 1 if spices salt = 1 and Tomato flavor = 1 then 1.000
6 1 if spices salt = 1 and BBQ flavor = 1 then 1.000
173
6 1 if spices salt = 1 and Cumin BBQ = 1 then 1.000
8 1 if spices salt = 1 and Hot sichuan = 1 then 1.000
12 1 if spices salt = 1 and Cheese corn flavor = 1 then 1.000
18 0.944 if Curry beef = 1 then 1.000
14 0.929 if Curry beef = 1 and Tomato flavor = 1 then 1.000
14 0.929 if Curry beef = 1 and Cheese corn flavor = 1 then 1.000
13 0.923 if Curry beef = 1 and Sauced beef flavor = 1 then 1.000
12 0.917 if spices salt = 1 and Sauced beef flavor = 1 then 1.000
11 0.909 if Tomato flavor = 1 and Cheese corn flavor = 1 then 1.000
10 0.9 if Kimchi flavor = 1 and Curry beef = 1 then 1.000
10 0.9 if Curry beef = 1 and Hot sichuan = 1 then 1.000
10 0.9 if Curry beef = 1 and Chives flavor = 1 then 1.000
Yolk Flavor Rule Set
1.000 = Yolk Flavor
ID Probability Rule
11 1 if Pork steak = 1 and Chives flavor = 1 then 1.000
10 1 if Pork steak = 1 and Sauced beef flavor = 1 then 1.000
6 1 if Crab flavor = 1 and Chicken flavor = 1 then 1.000
6 1 if Crab flavor = 1 and BBQ flavor = 1 then 1.000
5 1 if Pork steak = 1 and Crab flavor = 1 then 1.000
11 1 if Pork steak = 1 and Chicken flavor = 1 then 1.000
8 1 if Pork steak = 1 and Kimchi flavor = 1 then 1.000
5 1 if Pork steak = 1 and Tomato flavor = 1 then 1.000
11 1 if Pork steak = 1 and BBQ flavor = 1 then 1.000
11 1 if Pork steak = 1 and Cumin BBQ = 1 then 1.000
11 1 if Pork steak = 1 and Hot sichuan = 1 then 1.000
8 1 if Pork steak = 1 and Cheese corn flavor = 1 then 1.000
13 0.923 if Chicken flavor = 1 and Cumin BBQ = 1 then 1.000
13 0.923 if Chicken flavor = 1 and Chives flavor = 1 then 1.000
12 0.917 if Pork steak = 1 then 1.000
12 0.917 if Chicken flavor = 1 and Hot sichuan = 1 then 1.000
10 0.9 if Chicken flavor = 1 and Kimchi flavor = 1 then 1.000
10 0.9 if Kimchi flavor = 1 and BBQ flavor = 1 then 1.000
BBQ Flavor Rule Set
1.000 = BBQ Flavor
ID Probability Rule
11 1 if Pork steak = 1 and Hot sichuan = 1 then 1.000
8 1 if Pork steak = 1 and Cheese corn flavor = 1 then 1.000
11 1 if Pork steak = 1 and Chives flavor = 1 then 1.000
10 1 if Pork steak = 1 and Sauced beef flavor = 1 then 1.000
6 1 if Crab flavor = 1 and Yolk = 1 then 1.000
174
6 1 if Crab flavor = 1 and Chicken flavor = 1 then 1.000
12 1 if Yolk = 1 and Chicken flavor = 1 then 1.000
9 1 if Yolk = 1 and Kimchi flavor = 1 then 1.000
4 1 if Yolk = 1 and Curry beef = 1 then 1.000
6 1 if Yolk = 1 and Tomato flavor = 1 then 1.000
12 1 if Yolk = 1 then 1.000
12 1 if Yolk = 1 and Cumin BBQ = 1 then 1.000
11 1 if Yolk = 1 and Hot sichuan = 1 then 1.000
9 1 if Yolk = 1 and Cheese corn flavor = 1 then 1.000
12 1 if Yolk = 1 and Chives flavor = 1 then 1.000
11 1 if Yolk = 1 and Sauced beef flavor = 1 then 1.000
4 1 if spices salt = 1 and Chicken flavor = 1 then 1.000
5 1 if Chicken flavor = 1 and Pepper beef steak = 1 then 1.000
10 1 if Chicken flavor = 1 and Kimchi flavor = 1 then 1.000
6 1 if Chicken flavor = 1 and Curry beef = 1 then 1.000
8 1 if Chicken flavor = 1 and Tomato flavor = 1 then 1.000
14 1 if Chicken flavor = 1 then 1.000
13 1 if Chicken flavor = 1 and Cumin BBQ = 1 then 1.000
12 1 if Chicken flavor = 1 and Hot sichuan = 1 then 1.000
11 1 if Chicken flavor = 1 and Cheese corn flavor = 1 then 1.000
13 1 if Chicken flavor = 1 and Chives flavor = 1 then 1.000
13 1 if Chicken flavor = 1 and Sauced beef flavor = 1 then 1.000
5 1 if Pork steak = 1 and Crab flavor = 1 then 1.000
11 1 if Pork steak = 1 and Yolk = 1 then 1.000
11 1 if Pork steak = 1 and Chicken flavor = 1 then 1.000
8 1 if Pork steak = 1 and Kimchi flavor = 1 then 1.000
5 1 if Pork steak = 1 and Tomato flavor = 1 then 1.000
11 1 if Pork steak = 1 and Cumin BBQ = 1 then 1.000
15 0.933 if Cumin BBQ = 1 and Chives flavor = 1 then 1.000
14 0.929 if Cumin BBQ = 1 and Hot sichuan = 1 then 1.000
14 0.929 if Cumin BBQ = 1 and Sauced beef flavor = 1 then 1.000
14 0.929 if Hot sichuan = 1 and Chives flavor = 1 then 1.000
12 0.917 if Pork steak = 1 then 1.000
12 0.917 if Cumin BBQ = 1 and Cheese corn flavor = 1 then 1.000
11 0.909 if Kimchi flavor = 1 and Cumin BBQ = 1 then 1.000
Curry Flavor Rule Set
1.000 = Curry Flavor
ID Probability Rule
4 1 if spices salt = 1 and Chicken flavor = 1 then 1.000
5 1 if Chicken flavor = 1 and Pepper beef steak = 1 then 1.000
9 1 if Pepper beef steak = 1 and Kimchi flavor = 1 then 1.000
175
7 1 if Pepper beef steak = 1 and BBQ flavor = 1 then 1.000
7 1 if Pepper beef steak = 1 and Cumin BBQ = 1 then 1.000
9 1 if Pepper beef steak = 1 and Hot sichuan = 1 then 1.000
13 1 if Pepper beef steak = 1 and Cheese corn flavor = 1 then 1.000
9 1 if Pepper beef steak = 1 and Chives flavor = 1 then 1.000
12 1 if Pepper beef steak = 1 and Sauced beef flavor = 1 then 1.000
11 1 if Tomato flavor = 1 and Cheese corn flavor = 1 then 1.000
8 1 if spices salt = 1 and Kimchi flavor = 1 then 1.000
6 1 if spices salt = 1 and BBQ flavor = 1 then 1.000
6 1 if spices salt = 1 and Cumin BBQ = 1 then 1.000
8 1 if spices salt = 1 and Hot sichuan = 1 then 1.000
12 1 if spices salt = 1 and Cheese corn flavor = 1 then 1.000
8 1 if spices salt = 1 and Chives flavor = 1 then 1.000
17 0.941 if spices salt = 1 and Pepper beef steak = 1 then 1.000
13 0.923 if spices salt = 1 and Tomato flavor = 1 then 1.000
12 0.917 if spices salt = 1 and Sauced beef flavor = 1 then 1.000
Cumin BBQ Flavor Rule Set
1.000 = Cumin BBQ Flavor
ID Probability Rule
11 1 if Pork steak = 1 and Hot sichuan = 1 then 1.000
8 1 if Pork steak = 1 and Cheese corn flavor = 1 then 1.000
11 1 if Pork steak = 1 and Chives flavor = 1 then 1.000
10 1 if Pork steak = 1 and Sauced beef flavor = 1 then 1.000
6 1 if Crab flavor = 1 and Yolk = 1 then 1.000
6 1 if Crab flavor = 1 and Chicken flavor = 1 then 1.000
6 1 if Crab flavor = 1 and BBQ flavor = 1 then 1.000
12 1 if Yolk = 1 and Chicken flavor = 1 then 1.000
9 1 if Yolk = 1 and Kimchi flavor = 1 then 1.000
4 1 if Yolk = 1 and Curry beef = 1 then 1.000
12 1 if Yolk = 1 then 1.000
6 1 if Yolk = 1 and Tomato flavor = 1 then 1.000
12 1 if Yolk = 1 and BBQ flavor = 1 then 1.000
11 1 if Yolk = 1 and Hot sichuan = 1 then 1.000
9 1 if Yolk = 1 and Cheese corn flavor = 1 then 1.000
12 1 if Yolk = 1 and Chives flavor = 1 then 1.000
11 1 if Yolk = 1 and Sauced beef flavor = 1 then 1.000
10 1 if Chicken flavor = 1 and Kimchi flavor = 1 then 1.000
12 1 if Chicken flavor = 1 and Hot sichuan = 1 then 1.000
13 1 if Chicken flavor = 1 and Chives flavor = 1 then 1.000
10 1 if Kimchi flavor = 1 and BBQ flavor = 1 then 1.000
14 1 if BBQ flavor = 1 and Chives flavor = 1 then 1.000
176
14 1 if Hot sichuan = 1 and Chives flavor = 1 then 1.000
5 1 if Pork steak = 1 and Crab flavor = 1 then 1.000
11 1 if Pork steak = 1 and Yolk = 1 then 1.000
11 1 if Pork steak = 1 and Chicken flavor = 1 then 1.000
8 1 if Pork steak = 1 and Kimchi flavor = 1 then 1.000
5 1 if Pork steak = 1 and Tomato flavor = 1 then 1.000
11 1 if Pork steak = 1 and BBQ flavor = 1 then 1.000
14 0.929 if Chicken flavor = 1 and BBQ flavor = 1 then 1.000
14 0.929 if Chicken flavor = 1 then 1.000
14 0.929 if BBQ flavor = 1 and Hot sichuan = 1 then 1.000
13 0.923 if Chicken flavor = 1 and Sauced beef flavor = 1 then 1.000
12 0.917 if Pork steak = 1 then 1.000
11 0.909 if Chicken flavor = 1 and Cheese corn flavor = 1 then 1.000
Hot & Spice Salt Flavor Rule Set
1.000 = Hot & Spice Salt Flavor
ID Probability Rule
12 0.917 if Pepper beef steak = 1 and Sauced beef flavor = 1 then 1.000
13 0.923 if Pepper beef steak = 1 and Cheese corn flavor = 1 then 1.000
17 0.941 if Pepper beef steak = 1 and Curry beef = 1 then 1.000
Hot & Spice Sichuan Flavor Rule Set
1.000 = Hot & Spice Sichuan Flavor
ID Probability Rule
8 1 if Pork steak = 1 and Cheese corn flavor = 1 then 1.000
11 1 if Pork steak = 1 and Chives flavor = 1 then 1.000
10 1 if Pork steak = 1 and Sauced beef flavor = 1 then 1.000
5 1 if Pork steak = 1 and Crab flavor = 1 then 1.000
11 1 if Pork steak = 1 and Yolk = 1 then 1.000
11 1 if Pork steak = 1 and Chicken flavor = 1 then 1.000
8 1 if Pork steak = 1 and Kimchi flavor = 1 then 1.000
5 1 if Pork steak = 1 and Tomato flavor = 1 then 1.000
11 1 if Pork steak = 1 and BBQ flavor = 1 then 1.000
11 1 if Pork steak = 1 and Cumin BBQ = 1 then 1.000
15 0.933 if Cumin BBQ = 1 and Chives flavor = 1 then 1.000
14 0.929 if BBQ flavor = 1 and Cumin BBQ = 1 then 1.000
14 0.929 if BBQ flavor = 1 and Chives flavor = 1 then 1.000
14 0.929 if Cumin BBQ = 1 and Sauced beef flavor = 1 then 1.000
13 0.923 if Chicken flavor = 1 and Cumin BBQ = 1 then 1.000
13 0.923 if Chicken flavor = 1 and Chives flavor = 1 then 1.000
12 0.917 if Pork steak = 1 then 1.000
12 0.917 if Yolk = 1 and Chicken flavor = 1 then 1.000
12 0.917 if Yolk = 1 and BBQ flavor = 1 then 1.000
177
12 0.917 if Yolk = 1 and Cumin BBQ = 1 then 1.000
12 0.917 if Yolk = 1 and Chives flavor = 1 then 1.000
12 0.917 if Yolk = 1 then 1.000
12 0.917 if Cumin BBQ = 1 and Cheese corn flavor = 1 then 1.000
11 0.909 if Yolk = 1 and Sauced beef flavor = 1 then 1.000
11 0.909 if Kimchi flavor = 1 and Cumin BBQ = 1 then 1.000
10 0.9 if Chicken flavor = 1 and Kimchi flavor = 1 then 1.000
10 0.9 if Kimchi flavor = 1 and BBQ flavor = 1 then 1.000
Cheese Corn Flavor Rule Set
1.000 = Cheese Corn Flavor
ID Probability Rule
7 1 if Pepper beef steak = 1 and BBQ flavor = 1 then 1.000
9 1 if Pepper beef steak = 1 and Kimchi flavor = 1 then 1.000
6 1 if Chicken flavor = 1 and Curry beef = 1 then 1.000
5 1 if Chicken flavor = 1 and Pepper beef steak = 1 then 1.000
8 1 if spices salt = 1 and Chives flavor = 1 then 1.000
6 1 if spices salt = 1 and BBQ flavor = 1 then 1.000
8 1 if spices salt = 1 and Kimchi flavor = 1 then 1.000
4 1 if spices salt = 1 and Chicken flavor = 1 then 1.000
10 1 if Curry beef = 1 and Chives flavor = 1 then 1.000
8 1 if Curry beef = 1 and BBQ flavor = 1 then 1.000
10 1 if Kimchi flavor = 1 and Curry beef = 1 then 1.000
9 1 if Pepper beef steak = 1 and Chives flavor = 1 then 1.000
4 1 if Yolk = 1 and Curry beef = 1 then 1.000
13 0.923 if Curry beef = 1 and Sauced beef flavor = 1 then 1.000
12 0.917 if Pepper beef steak = 1 and Sauced beef flavor = 1 then 1.000
10 0.9 if Curry beef = 1 and Hot sichuan = 1 then 1.000 Table 8 Scoring information for Top 10 Rules in South West China Region Year 2013 2014 2015 2014 2015 2013 2015 2013 2014 2013
Month Jan May Sep Feb Jun Nov Mar Aug Dec May Tomato flavor 1 1 1 0 0 1 1 1 0 0
Crab flavor 1 0 0 0 0 1 1 0 1 0 Sauced beef 0 0 1 0 1 1 1 1 1 0
Cheese corn 0 0 1 0 0 1 0 1 1 0
BBQ flavor 0 0 1 0 1 0 1 1 0 0 Pepper beef steak 1 1 1 0 0 1 0 1 1 0
Chicken flavor 0 0 1 0 1 0 1 1 0 0 Curry beef 1 0 1 0 0 1 0 1 1 0
Cumin BBQ 0 0 1 0 1 0 1 0 1 0
spices salt 1 0 1 0 0 1 0 1 1 0
178
Pork steak 0 0 1 0 1 0 1 0 0 0 Yolk 0 0 1 0 1 0 1 0 0 0
Kimchi flavor 0 0 1 0 1 1 1 0 1 0 Chives flavor 0 0 1 0 1 1 1 0 1 0
Hot sichuan 0 0 1 0 1 0 1 0 1 0
Scoring Information Prediction 1 CBQ BQF
Confidence 1 0.92
9 0.93
3
Rule ID 1 212 209 Prediction 2 CVF CF
Confidence 2 0.92
9 0.90
9
Rule ID 2 213 293 Prediction 3 TF
Confidence 3 0.9 Rule ID 3 305