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- 2012-11-26
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Description: In the hidden space, using the least square loss function space $ proposed least squares support vector machine hidden# 0* &** 52H 8
Space with the implicit support to the
The amount of machine# &** 52H $ as an implicit least squares support vector machines do not need space to meet definite conditions $ kernel function extends SVM kernel function
Range of options
8
As a result of an implicit least squares loss function space $ least squares support vector machine optimization problem arising from the unconstrained convex quadratic programming for the $ than
Hidden space support vector machines produce more constrained convex quadratic programming solver
8
Simulation results show that the proposed method in computation time and the ability to promote a more implicit empty
Between the support vector machine there is a certain advantage
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最小二乘隐空间支持向量机.PDF
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