Stability analysis on rough set based feature evaluation

Qinghua Hu; Jinfu Liu; Daren Yu

doi:10.1007/978-3-540-79721-0_17

Stability analysis on rough set based feature evaluation

Qinghua Hu^*
, Jinfu Liu
, Daren Yu

^*Corresponding author for this work

School of Energy Science and Engineering

Harbin Institute of Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

8 Scopus citations

Abstract

Rough sets are widely used in feature evaluation and attribute reduction and a number of rough set based evaluation functions and search algorithms were reported. However, little attention has been paid to compute and compare stability of feature evaluation functions. In this work, we introduce three coefficients to calculate the stabilities of feature significance via perturbing samples. Experimental results show that entropy and fuzzy entropy based evaluation functions are more stable than the others and fuzzy rough set based functions are stable compared with the crisp functions. These results give a guideline to select feature evaluation for different applications.

Original language	English
Title of host publication	Rough Sets and Knowledge Technology - Third International Conference, RSKT 2008, Proceedings
Pages	88-96
Number of pages	9
DOIs	https://doi.org/10.1007/978-3-540-79721-0_17
State	Published - 2008
Event	3rd International Conference on Rough Sets and Knowledge Technology, RSKT 2008 - Chengdu, China Duration: 17 May 2008 → 19 May 2008

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	5009 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	3rd International Conference on Rough Sets and Knowledge Technology, RSKT 2008
Country/Territory	China
City	Chengdu
Period	17/05/08 → 19/05/08

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10.1007/978-3-540-79721-0_17

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Hu, Q., Liu, J., & Yu, D. (2008). Stability analysis on rough set based feature evaluation. In Rough Sets and Knowledge Technology - Third International Conference, RSKT 2008, Proceedings (pp. 88-96). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5009 LNAI). https://doi.org/10.1007/978-3-540-79721-0_17

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title = "Stability analysis on rough set based feature evaluation",

abstract = "Rough sets are widely used in feature evaluation and attribute reduction and a number of rough set based evaluation functions and search algorithms were reported. However, little attention has been paid to compute and compare stability of feature evaluation functions. In this work, we introduce three coefficients to calculate the stabilities of feature significance via perturbing samples. Experimental results show that entropy and fuzzy entropy based evaluation functions are more stable than the others and fuzzy rough set based functions are stable compared with the crisp functions. These results give a guideline to select feature evaluation for different applications.",

author = "Qinghua Hu and Jinfu Liu and Daren Yu",

year = "2008",

doi = "10.1007/978-3-540-79721-0\_17",

language = "英语",

isbn = "3540797203",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

pages = "88--96",

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note = "3rd International Conference on Rough Sets and Knowledge Technology, RSKT 2008 ; Conference date: 17-05-2008 Through 19-05-2008",

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Hu, Q, Liu, J & Yu, D 2008, Stability analysis on rough set based feature evaluation. in Rough Sets and Knowledge Technology - Third International Conference, RSKT 2008, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5009 LNAI, pp. 88-96, 3rd International Conference on Rough Sets and Knowledge Technology, RSKT 2008, Chengdu, China, 17/05/08. https://doi.org/10.1007/978-3-540-79721-0_17

Stability analysis on rough set based feature evaluation. / Hu, Qinghua; Liu, Jinfu ; Yu, Daren.
Rough Sets and Knowledge Technology - Third International Conference, RSKT 2008, Proceedings. 2008. p. 88-96 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5009 LNAI).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Liu, Jinfu

AU - Yu, Daren

PY - 2008

Y1 - 2008

N2 - Rough sets are widely used in feature evaluation and attribute reduction and a number of rough set based evaluation functions and search algorithms were reported. However, little attention has been paid to compute and compare stability of feature evaluation functions. In this work, we introduce three coefficients to calculate the stabilities of feature significance via perturbing samples. Experimental results show that entropy and fuzzy entropy based evaluation functions are more stable than the others and fuzzy rough set based functions are stable compared with the crisp functions. These results give a guideline to select feature evaluation for different applications.

AB - Rough sets are widely used in feature evaluation and attribute reduction and a number of rough set based evaluation functions and search algorithms were reported. However, little attention has been paid to compute and compare stability of feature evaluation functions. In this work, we introduce three coefficients to calculate the stabilities of feature significance via perturbing samples. Experimental results show that entropy and fuzzy entropy based evaluation functions are more stable than the others and fuzzy rough set based functions are stable compared with the crisp functions. These results give a guideline to select feature evaluation for different applications.

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ER -

Stability analysis on rough set based feature evaluation

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