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Transcript of SAP Predictive Analysis Library (PAL) Cheat Sheets - Save Time. Code more.
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SAP’s Predictive Analysis Library (PAL)Function Cheat Sheets
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Agenda
What Will Be Covered:
1. Predictive Analysis Library (PAL) Overview
2. PAL Function Cheat Sheets
1. Clustering/Classification/Regression
2. Association/Time Series/Preprocessing
3. Statistics/Social Network Analysis/Miscellaneous
3. About us
Predictive Analysis Library (PAL ) Overview
Just the term “SAP Predictive Analysis” can make the best analyst tremble in fear, as it’s a complicated topic to comprehend.
The “why” versus the “what” are the easier topics to grasp. The “how” is where people commonly hit unpassable roadblocks.
It can get overwhelming; SAP Predictive Analysis metrics & calculations are confusing, disjointed & constantly changing.
To help, SAP has grouped functions for particular topics together into the Application Function Library (AFL).
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For further information please refer to: http://help.sap.com/saphelp_hanaplatform/helpdata/en/65/2c5ada587d4a018aa4a4cde6ae1fc4/frameset.htm
Predictive Analysis Library (PAL ) Overview
SAP’s Predictive functions were grouped together in the AFL’s Predictive Analysis Library (PAL).
Add-on set of application functions that implement analysis algorithms. Makes executing clustering calculations w/ SAP HANA data easy & straightforward. Leverages HANA’s in-memory & near-linear parallelism performance for scoring, training, &
categorization; without data leaving the server. PAL can be accessed by SAP HANA SQL Script, which is an extension to SQL.
Adds control-flow capabilities & the ability to define complex application logic. Embeds predictive analytics into business applications. Contains universal predictive algorithms that execute directly against SAP HANA data. Enables up to 80% of the most use case common predictive scenarios.
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For further information please refer to: http://help.sap.com/hana/SAP_HANA_Predictive_Analysis_Library_PAL_en.pdf
Predictive Analysis Library (PAL ) Overview
PAL function algorithms are required for SAP HANA applications, based on market survey responses, & are usually available in other database products.
PAL includes classic and universal predictive analysis algorithms in nine data-mining function categories:
Clustering/Classification/Regression Association/Time Series/Preprocessing Statistics/Social Network Analysis/Miscellaneous
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Let’s now take a look at the PAL function algorithms in the following slides. A full detailed list can be found via the link below:
http://help.sap.com/hana/SAP_HANA_Predictive_Analysis_Library_PAL_en.pdf
For further information please refer to: http://help.sap.com/hana/SAP_HANA_Predictive_Analysis_Library_PAL_en.pdf
PAL Functions: Clustering
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Category PAL Algorithm Built-in Function Name
Clustering Affinity Propagation AP
Agglomerate Hierarchical Clustering HCAGGLOMERATE
Anomaly Detection ANOMALYDETECTION
Cluster Assignment CLUSTERASSIGNMENT
DBSCAN DBSCAN
Gaussian Mixture Model (GMM) GMM
K-Means KMEANS / VALIDATEKMEANS
K-Medians KMEDIANS
K-Medoids KMEDOIDS
LDA Estimation and Inference LDAESTIMATE / LDAINFERENCE
Self-Organizing Maps SELFORGMAP
Slight Silhouette SLIGHTSILHOUETTE
PAL Clustering Functions can be seen below:
For further information please refer to: http://help.sap.com/hana/SAP_HANA_Predictive_Analysis_Library_PAL_en.pdf
PAL Functions: Classification
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Category PAL Algorithm Built-in Function NameClassification Area Under Curve (AUC) AUC
Back Propagation Neural Network CREATEBPNN / PREDICTWITHBPNN
C4.5 Decision Tree CREATEDTWITHC45
CART Decision Tree CART
CHAID Decision Tree CREATEDTWITHCHAID
Confusion Matrix CONFUSIONMATRIX
KNN KNN
Logistic Regression (w/ Elastic Net Regularization) LOGISTICREGRESSION / FORECASTWITHLOGISTICR
Multi-Class Logistic Regression LRMCTR / LRMCTE
Naive Bayes NBCTRAIN / NBCPREDICT
Parameter Selection & Model Evaluation (PSME) PSME
Predict w/ Tree Model PREDICTWITHDT
Random Forest RANDOMFORESTTRAIN / RANDOMFORESTSCORING
Support Vector Machine SVMTRAIN / SVMPREDICT
PAL Classification Functions can be seen below:
For further information please refer to: http://help.sap.com/hana/SAP_HANA_Predictive_Analysis_Library_PAL_en.pdf
PAL Functions: Regression
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Category PAL Algorithm Built-in Function NameRegression Bi-Variate Geometric Regression GEOREGRESSION / FORECASTWITHGEOR
Bi-Variate Natural Logarithmic Regression LNREGRESSION / FORECASTWITHLNR
Exponential Regression EXPREGRESSION / FORECASTWITHEXPR
Multiple Linear Regression LRREGRESSION / FORECASTWITHLR
Polynomial Regression POLYNOMIALREGRESSION / FORECASTWITHPOLYNOMIALR
PAL Regression Functions can be seen below:
For further information please refer to: http://help.sap.com/hana/SAP_HANA_Predictive_Analysis_Library_PAL_en.pdf
PAL Functions: Association
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Category PAL Algorithm Built-in Function NameAssociation Apriori APRIORIRULE / LITEAPRIORIRULE / APRIORIRULE2
FP-Growth FPGROWTH
K-Optimal Rule Discovery (KORD) KORD
PAL Association Functions can be seen below:
For further information please refer to: http://help.sap.com/hana/SAP_HANA_Predictive_Analysis_Library_PAL_en.pdf
PAL Functions: Time Series
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Category PAL Algorithm Built-in Function NameTime Series ARIMA ARIMATRAIN / ARIMAFORECAST / ARIMAXFORECAST
Auto ARIMA AUTOARIMA
Brown Exponential Smoothing BROWNEXPSMOOTH
Croston’s Method CROSTON
Forecast Accuracy Measures ACCURACYMEASURES
Forecast Smoothing FORECASTSMOOTHING
Linear Regression w/ Damped Trend & Seasonal Adjust LRWITHSEASONALADJUST
Single Exponential Smoothing SINGLESMOOTH
Double Exponential Smoothing DOUBLESMOOTH
Triple Exponential Smoothing TRIPLESMOOTH
Seasonality Test SEASONALITYTEST
Trend Test TRENDTEST
White Noise Test WHITENOISETEST
PAL Time Series Functions can be seen below:
For further information please refer to: http://help.sap.com/hana/SAP_HANA_Predictive_Analysis_Library_PAL_en.pdf
PAL Functions: Preprocessing
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Category PAL Algorithm Built-in Function NamePreprocessing Binning BINNING
Binning Assignment BINNINGASSIGNMENT
Convert Category Type to Binary Vector CONV2BINARYVECTOR
Inter-Quartile Range Test IQRTEST
Partition PARTITION
Posterior Scaling POSTERIORSCALING
Principal Component Analysis (PCA) PCA / PCAPROJECTION
Random Distribution Sampling DISTRRANDOM
Sampling SAMPLING
Scaling Range SCALINGRANGE
Substitute Missing Values SUBSTITUTE_MISSING_VALUES
Variance Test VARIANCETEST
PAL Preprocessing Functions can be seen below:
For further information please refer to: http://help.sap.com/hana/SAP_HANA_Predictive_Analysis_Library_PAL_en.pdf
PAL Functions: Statistics
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Category PAL Algorithm Built-in Function NameStatistics Chi-Squared Test for Fitness CHISQTESTFIT
Chi-Squared Test for Independent CHISQTESTIND
Cumulative Distribution Function DISTRPROB
Distribution Fitting DISTRFIT / DISTRFITCENSORED
Grubbs’ Test GRUBBSTEST
Kaplan-Meier Survival Analysis KMSURV
Multivariate Statistics MULTIVARSTAT
Quantile Function DISTRQUANTILE
Univariate Statistics UNIVARSTAT
Variance Equal Test VAREQUALTEST
PAL Statistics Functions can be seen below:
For further information please refer to: http://help.sap.com/hana/SAP_HANA_Predictive_Analysis_Library_PAL_en.pdf
PAL Functions: Social Network Analysis
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Category PAL Algorithm Built-in Function NameSocial Network Analysis Link Prediction LINKPREDICTION
PAL Social Network Analysis Functions can be seen below:
For further information please refer to: http://help.sap.com/hana/SAP_HANA_Predictive_Analysis_Library_PAL_en.pdf
PAL Functions: Miscellaneous
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Category PAL Algorithm Built-in Function NameMiscellaneous ABC Analysis ABC
Weighted Score Table WEIGHTEDTABLE
PAL Miscellaneous Functions can be seen below:
For further information please refer to: http://help.sap.com/hana/SAP_HANA_Predictive_Analysis_Library_PAL_en.pdf
Success – You Completed The Lesson!
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Congratulations, you completed the lesson!
In this lesson you successfully learned:
1. Predictive Analysis Library (PAL) Overview
2. PAL Function Cheat Sheets
1. Clustering/Classification/Regression
2. Association/Time Series/Preprocessing
3. Statistics/Social Network Analysis/Miscellaneous
3. About us
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