most citedAnalytic Feature Selection for Support Vector Machines

2 citations · 2 across the 1 of their papers we have counts for

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1 paper

cs.LG2013★ 2 cited

Analytic Feature Selection for Support Vector Machines

Carly Stambaugh, Hui Yang, Felix Breuer

Support vector machines (SVMs) rely on the inherent geometry of a data set to classify training data. Because of this, we believe SVMs are an excellent candidate to guide the devel…