Hector Damian Mendez Davila

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In This work we prove a new theorem applicable to polynomial kernels for SVM classification tasks. This theorem relates the properties of the input space to the kernel function space. Thus, we find basic requirements for polynomial kernels if it is to linearly separate the data in feature space. Assuming the data in input space is separable by a polynomial(More)
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