Switch calibration.py to Use scipy's expit to Prevent Warnings (#12896)#12909
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rth merged 2 commits intoscikit-learn:masterfrom Jan 3, 2019
ZaydH:fix_issue_12896
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Switch calibration.py to Use scipy's expit to Prevent Warnings (#12896)#12909rth merged 2 commits intoscikit-learn:masterfrom ZaydH:fix_issue_12896
rth merged 2 commits intoscikit-learn:masterfrom
ZaydH:fix_issue_12896
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…it function instead of directly using np.exp
rth
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LGTM, Thanks @ZaydH!
There is one remaining call to np.exp in calibration.py. The function is also being used to calculate a logistic function in function _sigmoid_calibration (see inner function grad). However an intermediate result is being used elsewhere so I left that unchanged as I was not sure the standard for handling this within sklearn. If you let me know the standard, I can change that too.
I would say we leave it unchanged, given that exp is pretty expensive calculation and it would suboptimal to do this calculation twice when computing the gradient.
qinhanmin2014
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LGTM, thanks @ZaydH , waiting for CI
I think we can change this without tests and what's new
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This reverts commit 0c4d9d3.
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This reverts commit 0c4d9d3.
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Switch
calibration.pyto Use scipy'sexpitFunction to Prevent Possible Overflow WarningsReference Issues/PRs
Fixes #12896
What does this implement/fix? Explain your changes.
Previously, the logistic function was calculated via calls to
np.exp. This can in some cases lead to warnings due to overflow. This was fixed by changing the calls to scipy'sexpitfunction.Any other comments?
There is one remaining call to
np.expincalibration.py. The function is also being used to calculate a logistic function in function_sigmoid_calibration(see inner functiongrad). However an intermediate result is being used elsewhere so I left that unchanged as I was not sure the standard for handling this withinsklearn. If you let me know the standard, I can change that too.