Monday, September 20, 2010

Decision Trees

DECISION TREES: 'Classification and Decision Trees'(CART) Divides the training set into rectangles (partitions) based on simple rules and a measure of 'impurity.' (recursive partitioning) Rules and partitions can be visualized as a 'tree.' These rules can then be used to classify new data sets.

(Adapted from ‘The Elements of Statistical Learning ‘ Hasti, Tibshirani,Friedman)

RANDOM FORESTS: An ensemble of decision trees.

CHI-SQUARED AUTOMATIC INTERACTION DETECTION: characterized by the use of a chi-square test to stop decision tree splits. (CHAID) Requires more computational power than CART.

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