Hi Raga,
You may try approximating your kernel using Nystroem kernel approximator
(kernel_approximation.Nystroem) and then apply LDA to the transformed
feature vectors. If you choose dimensionality of the target space
(n_components) large enough (depending on your kernel and data),
Nystroem approximator should provide sufficiently good kernel
approximation for such combination to approximate GDA.
Raga Markely писал 2017-01-09 19:29:
Hello,
I wonder if scikit-learn has implementation for generalized
discriminant analysis using kernel approach?
http://www.kernel-machines.org/papers/upload_21840_GDA.pdf
I did some search, but couldn't find.
Thank you,
Raga
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