QUANTITATIVE ANALYSISFOR DECISION MAKINGREPORTER : LIGAYA AMOR O. LUMAWAGPROFESSOR : DR. RANDY TUDY DECISION TREE

ADVANTAGES OF DECISION TREE ANALYSIS

TRANSPARENCYSPECIFICITYCOMPREHENSIVE NATUREEASE OF USEFLEXIBILITYRESILIENCEVALIDATION

TRANSPARENCY

The use of separate nodes to denote user defined decisions, uncertainties, and end of process lends further clarity and transparency to the decision-making process.

SPECIFICITY

Ability to assign specific values to problem, decisions, and outcomes of each decision. Every possible scenario from a decision finds representation by a clear fork and node, enabling viewing all possible solutions clearly in a single view.Incorporation of monetary values to decision trees help make explicit the costs and benefits of different alternative courses of action.

COMPREHENSIVE NATURE

It allows for a comprehensive analysis of the consequences of each possible decision, such as what the decision leads to, whether it ends in uncertainty or a definite conclusion, or whether it leads to new issues for which the process needs repetition.

EASE OF USEProvides a graphical illustration of the problem and various alternatives in a simple and easy to understand format that requires no explanation.Break down data in an easy to understand illustrations, based on rules easily understood by humans. It also allow for classification of data without computation, can handle both continuous and categorical variables, and provide a clear indication of the most important fields for prediction or classification, all unmatched features when comparing this model to other compatible models such as support vector or logistic regression.

FLEXIBILITYDecision trees remain flexible to handle items with a mixture of real-valued and categorical features, and items with some missing features. Once constructed, they classify new items quickly.

RESILIENCE

Focuses on the relationship among various events and thereby, replicates the natural course of events, and as such, remains robust with little scope for errors, provided the inputted data is correct.

VALIDATION

Validate results of statistical tests. It naturally supports classification problems with more than two classes and by modification, handles regression problems.Provide a framework to quantify the values and probability of each possible outcome of a decision, allowing decision makers to make educated choices among the various alternatives.

THE MAJOR DISADVANTAGE OF DECISION TREESLOSS OF INNOVATION - only past experience and corporate habit go into the branching of choices; new ideas dont get much consideration. There is a tendency with trees to only consider paths that have been successful in the past, thus stultifying thought about changing situations.The trees are usually over-simple, not branched enough, and little consideration given to the thickness (value and probability) of each branch.

Decision trees assist managers in evaluating upcoming choices. The tree creates a visual representation of all possible outcomes, rewards and follow-up decisions in one document. Each subsequent decision resulting from the original choice is also depicted on the tree, so you can see the overall effect of any one decision. As you go through the tree and make choices, you will see a specific path from one node to another and the impact a decision made now could have down the road.

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