On A Variable Selection Method based on the Relationship between Discrimination Information and Principal Components
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- Yamamoto Toshiki
- University of Tsukuba
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- Sato-ilic Mika
- University of Tsukuba
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Description
Discrimination methods have been proposed by developing a discriminator used with data contains discrimination information. However, when the observed data is multivariate data the discrimination becomes more difficult. In order to solve this problem, a variable selection is important to improve the correct identification rate. In this paper, a new variable selection method is proposed through the principal components by using the relationship between discrimination information and principal components. Several numerical examples show a better performance of the proposed method.
Journal
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- Proceedings of the Fuzzy System Symposium
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Proceedings of the Fuzzy System Symposium 31 (0), 75-80, 2015
Japan Society for Fuzzy Theory and Intelligent Informatics
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Details 詳細情報について
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- CRID
- 1390001205673166080
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- NII Article ID
- 130005488376
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- NII Book ID
- AA12165648
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- ISSN
- 18820212
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- NDL BIB ID
- 026775875
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- Text Lang
- en
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- Data Source
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- JaLC
- NDL
- CiNii Articles
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- Abstract License Flag
- Disallowed