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Article:Feature Usability Index and Optimal Feature Subset Selection

by Debdoot Sheet, Jyotirmoy Chatterjee, Hrushikesh Garud
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 12 - Number 2
Year of Publication: 2010
Authors: Debdoot Sheet, Jyotirmoy Chatterjee, Hrushikesh Garud
10.5120/1650-2219

Debdoot Sheet, Jyotirmoy Chatterjee, Hrushikesh Garud . Article:Feature Usability Index and Optimal Feature Subset Selection. International Journal of Computer Applications. 12, 2 ( December 2010), 29-36. DOI=10.5120/1650-2219

@article{ 10.5120/1650-2219,
author = { Debdoot Sheet, Jyotirmoy Chatterjee, Hrushikesh Garud },
title = { Article:Feature Usability Index and Optimal Feature Subset Selection },
journal = { International Journal of Computer Applications },
issue_date = { December 2010 },
volume = { 12 },
number = { 2 },
month = { December },
year = { 2010 },
issn = { 0975-8887 },
pages = { 29-36 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume12/number2/1650-2219/ },
doi = { 10.5120/1650-2219 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:00:39.342840+05:30
%A Debdoot Sheet
%A Jyotirmoy Chatterjee
%A Hrushikesh Garud
%T Article:Feature Usability Index and Optimal Feature Subset Selection
%J International Journal of Computer Applications
%@ 0975-8887
%V 12
%N 2
%P 29-36
%D 2010
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Feature usability index is introduced here as a measure for evaluating classification efficacy of features. It is defined using measures of homogeneity, class specificity, and error in decision making. Homogeneity measures the extent of outlying observations, class specificity assesses the separation between distributions of different labeled classes, and error in decision making is computed using overlap in posteriori decision boundary. This is followed by feature ranking and optimal feature subset selection through ordering of features based on feature usability index and involves a complexity of O(DlogD) for D features. The results validating classifier independent feature ranking and optimal feature subset selection are also presented aong with a comparative analysis using χ2 statistics for feature selection.

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Index Terms

Computer Science
Information Sciences

Keywords

Feature ranking feature selection knowledge discovery knowledge engineering pattern recognition

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