Decision Tree Inudction

Decision Tree Inudction

Roberta Siciliano (University of Naples Federico II, Italy) and Claudio Conversano (University of Cassino, Italy)
Copyright: © 2005 |Pages: 6
DOI: 10.4018/978-1-59140-557-3.ch068
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Abstract

Decision Tree Induction (DTI) is an important step of the segmentation methodology. It can be viewed as a tool for the analysis of large datasets characterized by high dimensionality and nonstandard structure. Segmentation follows a nonparametric approach, since no hypotheses are made on the variable distribution. The resulting model has the structure of a tree graph. It is considered a supervised method, since a response criterion variable is explained by a set of predictors.

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