Some investigations on the LDA when handling large number of variable

Linear discriminant analysis (LDA) has been used widely in many classification problems.This paper discusses the performances of LDA when the classification problems face with large number of variables.Two common strategies for constructing LDA are investigated: (i) some selected variables are use...

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Main Authors: Hamid, Hashibah, Mahat, Nor Idayu
格式: Conference or Workshop Item
語言:English
出版: 2010
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在線閱讀:http://repo.uum.edu.my/5193/1/hashibah1-1.pdf
http://repo.uum.edu.my/5193/
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機構: Universiti Utara Malaysia
語言: English
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總結:Linear discriminant analysis (LDA) has been used widely in many classification problems.This paper discusses the performances of LDA when the classification problems face with large number of variables.Two common strategies for constructing LDA are investigated: (i) some selected variables are used and (ii) all variables are combined systematically, in such a way that the performance of LDA is optimised.These strategies are studied on some example data sets through the leave-one-out procedure.The results indicate that, the performance of LDA with the combination of variables is the best based on the leave-one-out error rate.