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Conditional Mutual Information Based Feature Selection for Classification Task
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SYSNO ASEP 0085611 Document Type J - Journal Article R&D Document Type Journal Article Subsidiary J Ostatní články Title Conditional Mutual Information Based Feature Selection for Classification Task Title Výběr příznaků pro klasifikaci založený na podmíněné vzájemné informaci Author(s) Novovičová, Jana (UTIA-B)
Somol, Petr (UTIA-B) RID
Haindl, Michal (UTIA-B) RID, ORCID
Pudil, Pavel (UTIA-B) RIDSource Title Lecture Notes in Computer Science - ISSN 0302-9743
Roč. 45, č. 4756 (2007), s. 417-426Number of pages 10 s. Language eng - English Country DE - Germany Keywords Pattern classification ; feature selection ; conditional mutual information ; text categorization Subject RIV BB - Applied Statistics, Operational Research R&D Projects 1M0572 GA MŠMT - Ministry of Education, Youth and Sports (MEYS) IAA2075302 GA AV ČR - Academy of Sciences of the Czech Republic (AV ČR) CEZ AV0Z10750506 - UTIA-B (2005-2011) Annotation We propose a sequential forward feature selection method to find a subset of features that are most relevant to the classification task. Our approach uses novel estimation of the conditional mutual information between candidate feature and classes, given a subset of already selected features which is utilized as a classifier independent criterion for evaluation of feature subsets. The proposed mMIFS-U algorithm is applied to text classification problem and compared with MIFS method and MIFS-U method proposed by Battiti and Kwak and Choi, respectively. Our feature selection algorithm outperforms MIFS method and MIFS-U in experiments on high dimensional Reuters textual data. Workplace Institute of Information Theory and Automation Contact Markéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201. Year of Publishing 2008
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