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...
محفوظ في:
| المؤلفون الرئيسيون: | , |
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| التنسيق: | Conference or Workshop Item |
| اللغة: | English |
| منشور في: |
2010
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| الموضوعات: | |
| الوصول للمادة أونلاين: | http://repo.uum.edu.my/5193/1/hashibah1-1.pdf http://repo.uum.edu.my/5193/ |
| الوسوم: |
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| الملخص: | 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. |
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