An experimental study on feature subset selection methods

Chulmin Yun, Donghyuk Shin, Hyunsung Jo, Jihoon Yang, Saejoon Kim

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

17 Scopus citations

Abstract

In the field of machine learning and pattern recognition, feature subset selection is an important area, where many approaches have been proposed. In this paper, we choose some feature selection algorithms and analyze their performance using various datasets from public domain. We measured the number of reduced features and the improvement of learning performance with chosen feature selection methods, then evaluated and compared each method on the basis of these measurements.

Original languageEnglish (US)
Title of host publicationCIT 2007
Subtitle of host publication7th IEEE International Conference on Computer and Information Technology
Pages77-82
Number of pages6
DOIs
StatePublished - 2007
EventCIT 2007: 7th IEEE International Conference on Computer and Information Technology - Aizu-Wakamatsu, Fukushima, Japan
Duration: Oct 16 2007Oct 19 2007

Publication series

NameCIT 2007: 7th IEEE International Conference on Computer and Information Technology

Conference

ConferenceCIT 2007: 7th IEEE International Conference on Computer and Information Technology
CountryJapan
CityAizu-Wakamatsu, Fukushima
Period10/16/0710/19/07

ASJC Scopus subject areas

  • Computer Science Applications
  • Information Systems
  • Software
  • Mathematics(all)

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