[scikit-learn] PR #13003: [MRG] Add Tensor Sketch algorithm to Kernel Approximation module

[Daniel López-Sánchez]

Dear all,

I recently posted a PR
<https://github.com/scikit-learn/scikit-learn/pull/13003> which adds the
Tensor Sketch algorithm [1] to the Kernel Approximation module of
Scikit-learn.

I believe this new feature makes the Kernel Approximation module more
complete by providing a data-independent method for polynomial kernel
approximation, as the currently included methods either require access to
training data (Nystroem) or do not work with polynomial kernels. The
implementation has been tested to provide the same results as the original
Matlab implementation provided by the author of [1].

I would appreciate any feedback you can provide,

Regards,

[1] Pham, N., & Pagh, R. (2013, August). Fast and scalable polynomial
kernels via explicit feature maps. In Proceedings of the 19th ACM SIGKDD
international conference on Knowledge discovery and data mining (pp.
239-247). ACM.

*Daniel López Sánchez* <https://github.com/lopelh>
lope at usal.es / (+34) 687174328

BISITE Research Group (http://bisite.usal.es <http://bisite.usal.es/en>)
Edificio I+D+i Universidad de Salamanca, C/ Espejo S/N, 37007
Salamanca, Spain
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