168 DATA MINING AND KNOWLEDGE DISCOVERY HANDBOOK There are various top–down decision trees inducers such as ID3 (Quinlan, 1986), (Quinlan, 1993), CART (Breiman et al., 1984). Some consist of two conceptual phases: growing and pruning ( and CART). Other inducers perform only the growing phase.
Decision Tree Classification: Decision tree builds classification or regression models in the form of a tree structure. It breaks down a dataset into smaller and smaller subsets while at the same time an associated decision tree is incrementally developed. The final result is a tree with decision nodes and leaf nodes. A decision node ( ...
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Data Mining and Predictive Modeling with Excel 2007 6 Casualty Actuarial Society Forum, Winter 2009 This can be used to predict zeroclaim status for personal automobile insurance customer. For example, a table can be created that shows age, gender, marital status and if the customer had zero claims in a given time period . The Analyze Key ...
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Decision Trees. Classification and Regression Trees or CART for short is a term introduced by Leo Breiman to refer to Decision Tree algorithms that can be used for classification or regression predictive modeling problems.. Classically, this algorithm is referred to as "decision trees", but on some platforms like R they are referred to by the more modern term CART.
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Wiley Sons, Inc. WIREs Data Mining Knowl Discov 2011 1 14–23 DOI: / CLASSIFICATION TREES I ... Prune the tree with the CART method. CHAID15 employs yet another strategy. If X is an ordered variable, its data values in the node are ... Table 1 summarizes the features of the algorithms. To see how the algorithms perform in a real ap
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