Presentation 2011-03-10
Optimization in Pattern Classifier Design
Takio KURITA, Kenji NISHIDA, Akinori HIDAKA, Tetsu MATSUKAWA,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) To design a pattern classifier which works effectively in real world applications, we have to decide the model of the classifier and the features used by the classifier. Usually the designer of the classifier decides them by trial and error depending on the task. To automate this trial and error process, the system has to find the optimum classifier among the candidates of the classifiers with different models and features. An optimization method is necessary to find the optimum classifiers because the number of candidates is usually very large. This paper introduces some examples of optimization in pattern classifier design.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) model selection / feature selection / optimization / random sampling / particle swarm optimization
Paper # PRMU2010-251
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Committee PRMU
Conference Date 2011/3/3(1days)
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Paper Information
Registration To Pattern Recognition and Media Understanding (PRMU)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Optimization in Pattern Classifier Design
Sub Title (in English)
Keyword(1) model selection
Keyword(2) feature selection
Keyword(3) optimization
Keyword(4) random sampling
Keyword(5) particle swarm optimization
1st Author's Name Takio KURITA
1st Author's Affiliation Hiroshima University()
2nd Author's Name Kenji NISHIDA
2nd Author's Affiliation The National Institute of Advanced Industrial Science and Technology (AIST)
3rd Author's Name Akinori HIDAKA
3rd Author's Affiliation Tokyo Denki University
4th Author's Name Tetsu MATSUKAWA
4th Author's Affiliation University of Tsukuba
Date 2011-03-10
Paper # PRMU2010-251
Volume (vol) vol.110
Number (no) 467
Page pp.pp.-
#Pages 6
Date of Issue