Pruning multivariate decision trees by hyperplane merging

Miroslav Kubat, Doris Flotzinger

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

Several techniques for induction of multivariate decision trees have been published in the last couple of years. Internal nodes of such trees typically contain binary tests questioning to what side of a hyperplane the example lies. Most of these algorithms use cut-off pruning mechanisms similar to those of traditional decision trees. Nearly unexplored remains the large domain of substitutional pruning methods, where a new decision test (derived from previous decision tests) replaces a subtree. This paper presents an approach to multivariate-tree pruning based on merging the decision hyperplanes, and demonstrates its performance on artificial and benchmark data.

Original languageEnglish (US)
Title of host publicationMachine Learning
Subtitle of host publicationECML-95 - 8th European Conference on Machine Learning, 1995, Proceedings
EditorsNada Lavrac, Stefan Wrobel
PublisherSpringer Verlag
Pages190-199
Number of pages10
ISBN (Print)3540592865, 9783540592860
DOIs
StatePublished - Jan 1 1995
Externally publishedYes
Event8th European Conference on Machine Learning, ECML 1995 - Heraclion, Greece
Duration: Apr 25 1995Apr 27 1995

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume912
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other8th European Conference on Machine Learning, ECML 1995
CountryGreece
CityHeraclion
Period4/25/954/27/95

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Kubat, M., & Flotzinger, D. (1995). Pruning multivariate decision trees by hyperplane merging. In N. Lavrac, & S. Wrobel (Eds.), Machine Learning: ECML-95 - 8th European Conference on Machine Learning, 1995, Proceedings (pp. 190-199). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 912). Springer Verlag. https://doi.org/10.1007/3-540-59286-5_58