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 _______________________________________________ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn