MNT Speed up plot_sparse_logistic_regression_20newsgroups.py#21773
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ogrisel merged 1 commit intoscikit-learn:mainfrom Nov 26, 2021
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Here's the graph for before: Here's after: |
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On the CI, the change does not show the improvement but actually a slowdown (30 seconds instead of 20 seconds). I assume that here there is some convergence issue that reducing the number of samples does not mean necessarily that we will speed up the convergence. Quite fun as well that scaling data make things worse. |
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It might only be bad luck regarding the node that we got on the CI thought. Locally, I can observe the speed up |
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Jokes aside, I've observed the speedup running multiple times locally. |
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Hello! First time contributing. Please tell me if I have done something wrong! Thank you!
Reference Issues/PRs
Fixes #21598
What does this implement/fix? Explain your changes.
Specifically, speed up
examples/linear_model/plot_sparse_logistic_regression_20newsgroups.pyfrom 18.05 seconds to 4.59 seconds.I've updated the number of epochs and training labels to speed it up. Also confirmed the expected result where multinomial logistic regression is more accurate and faster than 1 vs all L1 logistic regression.
Any other comments?