kernel-pca

Description: Compute kernel-based eigenvectors for a set of training examples.

Usage: kernel-pca [options] -train <filename>

Input:

Output: An RDB matrix in which each column corresponds to an eigenvector. Eigenvectors are normalized so that the dot product of the eigenvector with itself equals the reciprocal of the corresponding eigenvalue. In the output, the eigenvectors are sorted by increasing magnitude.

Options:

The following six options modify the base kernel function. The operations occur in the order listed below.

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