Efficient Feature Subset Selection for Support Vector Machines
نویسندگان
چکیده
Support vector machines can be regarded as algorithms for compressing information about class membership into a few support vectors with clear geometric interpretation. It is tempting to use this compressed information to select the most relevant input features. In this paper we present a method for doing so and provide evidence that it selects high-quality feature sets at a fraction of the costs of classical methods.
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