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SVM: do we need the polynomial kernel #445

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mfeurer opened this issue Mar 22, 2018 · 4 comments
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SVM: do we need the polynomial kernel #445

mfeurer opened this issue Mar 22, 2018 · 4 comments
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enhancement A new improvement or feature

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@mfeurer
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mfeurer commented Mar 22, 2018

in initial experiments it is way slower than the RBF kernel.

@VladimirGl
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It also sometimes causes hangs for me then use ask on multithread mode (so I have separate model fitters and one ensembler).
So it was killed by time limits inside models fitters, but then I call refit on ensembler thread on whole data on, or on different folds (if use external cv) it never stops (may be related to some data scaling issues, not sure). I just set max number of iterations to couple of thousands instead of -1 to avoid this.

@mfeurer
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mfeurer commented Nov 26, 2020

Another related question: do we need to apply calibration via Platt Scaling to SVMs? Getting the most out of ensemble selection suggests that this is not necessary, so the time required to calibrate the SVM might rather be spent on searching for better hyperparameters.

@franchuterivera franchuterivera added the enhancement A new improvement or feature label Feb 17, 2021
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github-actions bot commented May 5, 2021

This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs for the next 7 days. Thank you for your contributions.

@mfeurer
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mfeurer commented Jan 31, 2022

Closing, see #1314 for the reasoning.

@mfeurer mfeurer closed this as completed Jan 31, 2022
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