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Does It Make Sense to Develop New Feature Selection Methods?
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SYSNO ASEP 0085720 Document Type V - Research Report R&D Document Type The record was not marked in the RIV Title Does It Make Sense to Develop New Feature Selection Methods? Title Má smysl vyvíjet nové metody výběru příznaků? Author(s) Somol, Petr (UTIA-B) RID
Novovičová, Jana (UTIA-B)Issue data Praha: ÚTIA AV ČR, 2007 Series Research Report Series number 2193 Number of pages 11 s. Language eng - English Country CZ - Czech Republic Keywords feature selection ; subset search ; search methods ; performance estimation ; classification accuracy Subject RIV BB - Applied Statistics, Operational Research R&D Projects 2C06019 GA MŠMT - Ministry of Education, Youth and Sports (MEYS) 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 One of hot topics discussed recently in relation to pattern recognition techniques is the question of actual performance of modern feature selection methods. Feature selection has been a highly active area of research in recent years due to its potential to improve both the performance and economy of automatic decision systems in various applicational fields, with medical diagnosis being among the most prominent. Feature selection may also improve the performance of classifiers learned from limited data, or contribute to model interpretability. The number of available methods and methodologies has grown rapidly while promising important improvements. Yet recently many authors put this development in question, claiming that simpler older tools show to be actually better than complex modern ones -- which, despite promises, are claimed to actually fail in real-world applications. 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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