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June 7, 2020 13:28
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Random Fourier Features comparison between shogun and sklearn
that is probably for high dimensional data then?
Ok thanks for the formula, seems ok then. Still you want to compare against shogun's kernel not your own
Will be updated, be assured
Looks like it's done!
Looks good now :)
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About the bandwidth, I've seen
np.log(100)
in our ipynb notebooks so I went with that(for ex: Gaussian Kernel in Classification.ipynb).Next, here's what "get_width" gives
return std::exp(m_log_width * 2.0) * 2.0
.