[MRG] FIX ignore null weight when computing estimator error in AdaBoostRegressor #14294
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BTW, this seems related to #14286 which investigates a similar issue with SVM. |
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ping @rth @jeremiedbb I think that you are the best to review this bug fix. |
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Not using points with zero weight to compute the error seems fair.
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besides minor comments, LGTM.
Co-Authored-By: jeremiedbb <[email protected]>
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@adrinjalali I'm pinging you aggressively ;) |
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I need to double check a few things before I can be sure about its correctness and completeness. But I was wondering if it'd be easier to mask the samples and the sample weight right at the beginning of the fit, and continue with all of what's left.
P.S. thanks for the very aggressive ping :P
Nop because the bootstrapping will lead to different results since the input data will be different due to masking. |
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@adrinjalali Any other comments? |
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Other than the small nit, LGTM, thanks @glemaitre
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Ready to be merged @adrinjalali @jeremiedbb |
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Thanks @glemaitre :) |
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AdaBoostRegressor suffers from a bug where the error was normalized using the max of the absolute error on all prediction even if they were corresponding to a null-weight in
sample_weigth