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ENH Add mean_pinball_loss metric for quantile regression #19415
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Thanks @sdpython! Here is a first pass of review comments:
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Thanks, I find the updated example very interesting.
@sdpython @lorentzenchr I pushed the renaming in my last commits. I think I also addressed most of the pending review comments. Let me know what you think. |
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@ogrisel Accompanying you improving examples is a pleasure and a lot of fun. Now I learned how to highlight cells in displayed pandas tables:smiley:
I googled after your comment and found this solution on stackoverflow :) |
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LGTM
Co-authored-by: Christian Lorentzen <lorentzen.ch@gmail.com>
The CI failure of |
Thanks for the PR @sdpython! and @lorentzenchr for the reviews :) |
Should this be median pinball loss for alpha=0.5/tau=0.5 (as per https://www.tensorflow.org/addons/api_docs/python/tfa/losses/pinball_loss)? |
This PR implemented the mean of the pinball loss as a metric, which equals 1/2 * absolute loss for alpha=0.5 (which elicits the median). I think the tensorflow fomula has a typo (i.e. is incorrect). |
hi there, I noticed that when my pandas dataframe has more than 10,000 rows, I get an out-of-memory error. Why does this occur and is there a way around it? |
Reference Issues/PRs
Example: Fixes #18911.
What does this implement/fix?
Add function pinball_error as a new regression scoring function used to estimate quantile regression with quantile != 0.5.