Sparse multinomial kernel discriminant analysis (sMKDA)
نویسندگان
چکیده
منابع مشابه
Sparse multinomial kernel discriminant analysis (sMKDA)
Dimensionality reduction via canonical variate analysis (CVA) is important for pattern recognition and has been extended variously to permit more flexibility, e.g. by “kernelizing” the formulation. This can lead to over-fitting, usually ameliorated by regularization. Here, a method for sparse, multinomial kernel discriminant analysis (sMKDA) is proposed, using a sparse basis to control complexi...
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ژورنال
عنوان ژورنال: Pattern Recognition
سال: 2009
ISSN: 0031-3203
DOI: 10.1016/j.patcog.2009.01.025