en
Proceedings chapter
Open access
English

Computing and using the deviance with classification trees

ContributorsRitschard, Gilbertorcid
Published inCOMPSTAT 2006 - Proceedings in Computational Statistics, Editors Rizzi, Alfredo and Vichi, Maurizio, p. 55-66
Presented at Berlin, 2006
Publication date2006
Abstract

The reliability of induced classification trees is most often evaluated by means of the error rate. Whether computed on test data or through cross-validation, this error rate is suited for classification purposes. We claim that it is, however, a partial indicator only of the quality of the knowledge provided by trees and that there is a need for additional indicators. For example, the error rate is not representative of the quality of the description provided. In this paper we focus on this descriptive aspect. We consider the deviance as a goodness-of-fit statistic that attempts to measure how well the tree is at reproducing the conditional distribution of the response variable for each possible profile (rather than the individual response value for each case) and we discuss various statistical tests that can be derived from them. Special attention is devoted to computational aspects.

Keywords
  • Classification tree
  • Deviance
  • Goodness-of-fit
  • Chi-square statistics
  • BIC
Citation (ISO format)
RITSCHARD, Gilbert. Computing and using the deviance with classification trees. In: COMPSTAT 2006 - Proceedings in Computational Statistics. Berlin. [s.l.] : [s.n.], 2006. p. 55–66. doi: 10.1007/978-3-7908-1709-6_5
Main files (1)
Proceedings chapter
accessLevelPublic
Identifiers
571views
724downloads

Technical informations

Creation12/01/2009 3:28:11 PM
First validation12/01/2009 3:28:11 PM
Update time03/14/2023 3:19:10 PM
Status update03/14/2023 3:19:09 PM
Last indexation05/02/2024 11:24:37 AM
All rights reserved by Archive ouverte UNIGE and the University of GenevaunigeBlack