Invariant optimal feature selection: A distance discriminant and feature ranking based solution
نویسندگان
چکیده
منابع مشابه
Invariant optimal feature selection: A distance discriminant and feature ranking based solution
The goal of feature selection is to find the optimal subset consisting of m features chosen from the total n features. One critical problem for many feature selection methods is that an exhaustive search strategy has to be applied to seek the best subset among all the possible ( n m ) feature subsets, which usually results in a considerably high computational complexity. The alternative subopti...
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The performance of a speech recogniser, or of any other pattern classifier, strongly depends on the input features: to obtain a good performance, the feature set needs to be both highly discriminative and compact. Linear discriminant analysis (LDA) is a common data-driven method used to find linear transformations that map large feature vectors onto smaller ones while retaining most of the disc...
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ژورنال
عنوان ژورنال: Pattern Recognition
سال: 2008
ISSN: 0031-3203
DOI: 10.1016/j.patcog.2007.10.018