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Evaluating Stability and Comparing Output of Feature Selectors that Optimize Feature Subset Cardinality
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SYSNO ASEP 0348726 Document Type J - Journal Article R&D Document Type Journal Article Subsidiary J Článek ve WOS Title Evaluating Stability and Comparing Output of Feature Selectors that Optimize Feature Subset Cardinality Author(s) Somol, Petr (UTIA-B) RID
Novovičová, Jana (UTIA-B)Source Title IEEE Transactions on Pattern Analysis and Machine Intelligence. - : IEEE Computer Society - ISSN 0162-8828
Roč. 32, č. 11 (2010), s. 1921-1939Number of pages 19 s. Language eng - English Country US - United States Keywords feature selection ; feature stability ; stability measures ; similarity measures ; sequential search ; individual ranking ; feature subset-size optimization ; high dimensionality ; small sample size Subject RIV BD - Theory of Information R&D Projects 1M0572 GA MŠMT - Ministry of Education, Youth and Sports (MEYS) GA102/08/0593 GA ČR - Czech Science Foundation (CSF) GA102/07/1594 GA ČR - Czech Science Foundation (CSF) CEZ AV0Z10750506 - UTIA-B (2005-2011) UT WOS 000281990900001 EID SCOPUS 78149286082 DOI 10.1109/TPAMI.2010.34. Annotation Stability (robustness) of feature selection methods is a topic of recent interest, yet often neglected importance, with direct impact on the reliability of machine learning systems. We investigate the problem of evaluating the stability of feature selection processes yielding subsets of varying size. We introduce several novel feature selection stability measures and adjust some existing measures in a unifying framework that offers broad insight into the stability problem. We study in detail the properties of considered measures and demonstrate on various examples what information about the feature selection process can be gained. We also introduce an alternative approach to feature selection evaluation in the form of measures that enable comparing the similarity of two feature selection processes. These measures enable comparing, e.g., the output of two feature selection methods or two runs of one method with different parameters. Workplace Institute of Information Theory and Automation Contact Markéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201. Year of Publishing 2011
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