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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)