Feature selection using consistency measure

Manoranjan Dash, Huan Liu, Hiroshi Motoda

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

1 Scopus citations

Abstract

Feature selection methods search for an “optimal” subset of features. Many methods exist. We evaluate consistency measure along with different search techniques applied in the literature and suggest a guideline of its use.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Verlag
Pages319-320
Number of pages2
Volume1721
ISBN (Print)354066713X, 9783540667131
DOIs
StatePublished - 1999
Externally publishedYes
Event2nd International Conference on Discovery Science, DS 1999 - Tokyo, Japan
Duration: Dec 6 1999Dec 8 1999

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume1721
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other2nd International Conference on Discovery Science, DS 1999
CountryJapan
CityTokyo
Period12/6/9912/8/99

    Fingerprint

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Dash, M., Liu, H., & Motoda, H. (1999). Feature selection using consistency measure. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1721, pp. 319-320). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1721). Springer Verlag. https://doi.org/10.1007/3-540-46846-3_30