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9

ESANN
2004

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Fuzzy LP-SVMs for Multiclass Problems

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Fuzzy LP-SVMs for Multiclass Problems

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Abstract. In this paper, we propose fuzzy linear programming support vector machines (LP-SVMs) that resolve unclassifiable regions for multiclass problems. Namely, in the directions orthogonal to the decision functions obtained by training the LP-SVM, we define membership functions. Then by the minimum or average operation for these membership functions we define a membership function for each class. We evaluate one-against-all and pairwise fuzzy LP-SVMs for some benchmark data sets and demonstrate the superiority of our fuzzy LP-SVMs over conventional LP-SVMs.

Shigeo Abe

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Added	30 Oct 2010
Updated	30 Oct 2010
Type	Conference
Year	2004
Where	ESANN
Authors	Shigeo Abe

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