Description: The algorithm will be practical problems through the nonlinear transformation to high-dimensional feature space, in high-dimensional space in the structure of linear discriminant function to replace the original space of nonlinear discriminant function, it can guarantee the machine has better generalization ability At the same time, it is cleverly solved the problem dimension, the algorithm complexity has nothing to do with the sample dimension
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@linear
.......\char.m
.......\display.m
.......\evaluate.m
.......\linear.m
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