Algorithms for constructing of decision trees

Mikhail Moshkov*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

Decision trees are widely used in different applications for problem solving and for knowledge representation. In the paper algorithms for decision tree constructing with bounds on complexity and precision are considered. In these algorithms different measures for time complexity of decision trees and different measures for uncertainty of decision tables are used. New results about precision of polynomial approximate algorithms for covering problem solving [1, 2] show that some of considered algorithms for decision tree constructing are, apparently, close to unimprovable.

Original languageEnglish (US)
Title of host publicationPrinciples of Data Mining and Knowledge Discovery - 1st European Symposium, PKDD 1997, Proceedings
EditorsJan Komorowski, Jan Zytkow
PublisherSpringer Verlag
Pages335-342
Number of pages8
ISBN (Print)3540632239, 9783540632238
StatePublished - Jan 1 1997
Event1st European Symposium on Principles of Data Mining and Knowledge Discovery, PKDD 1997 - Trondheim, Norway
Duration: Jun 24 1997Jun 27 1997

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume1263
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other1st European Symposium on Principles of Data Mining and Knowledge Discovery, PKDD 1997
CountryNorway
CityTrondheim
Period06/24/9706/27/97

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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