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	STUDIA INFORMATICA - Issue no. 1 / 2006

	Article:	NONLINEAR EVOLUTIONARY SUPPORT VECTOR MACHINES. APPLICATION TO CLASSIFICATION. Authors: RUXANDRA STOEAN, D. DUMITRESCU, CĂTĂLIN STOEAN.


	Abstract: Support vector machines are a modern and very e�cient learning heuristic. However, their internal engine relies on not very easy or common mathematical concepts. The paper presents a newly developed simpler de- sign of the engine, built through the means of evolutionary computation, in the context of nonlinear support vector machines. Experiments are carried on fictitious 2-dimensional points data sets and demonstrate once again the promise of the new approach.




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