Tree‐structured classifiers | Zendy

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Tree‐structured classifiers

Author(s) -

Loh WeiYin

Publication year - 2010

Publication title -

wiley interdisciplinary reviews: computational statistics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.693

H-Index - 38

eISSN - 1939-0068

pISSN - 1939-5108

DOI - 10.1002/wics.86

Subject(s) - cart , decision tree , decision tree learning , computer science , artificial intelligence , machine learning , tree (set theory) , logistic model tree , classifier (uml) , regression , exploratory data analysis , data mining , statistics , mathematics , geography , mathematical analysis , archaeology

A tree‐structured classifier is a decision tree for predicting a class variable from one or more predictor variables. THAID was the first such algorithm. This article focuses on the classification and regression trees CART ® C4.5, and GUIDE methods. The algorithms are briefly reviewed and their similarities and differences are compared on a real data set and by simulation. Copyright © 2010 John Wiley & Sons, Inc. This article is categorized under: Statistical Learning and Exploratory Methods of the Data Sciences > Classification and Regression Trees (CART)

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