Fix to inelegant failure of RandomTreesEmbedding.transform when not fitted#12965
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qinhanmin2014 merged 1 commit intoscikit-learn:masterfrom Jan 13, 2019
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…coder_ missing when it hasn't first been fit. This message doesn't tell the user what to do to fix the problem. I've added a check for .one_hot_encoder_ using the standard check_is_fitted method that is used by most other classes with a fit and predict/transform. This should make it clear that the instance isn't yet fit.
qinhanmin2014
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thanks @finnoshea
I think we'll rely on a common test to test these things.
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…not fitted (scikit-learn#12965)" This reverts commit d857e78.
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…not fitted (scikit-learn#12965)" This reverts commit d857e78.
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RandomTreesEmbedding.transform fails with a message about .one_hot_encoder_ missing when it hasn't first been fit. This message doesn't tell the user what to do to fix the problem. I've added a check for .one_hot_encoder_ using the standard check_is_fitted method that is used by most other classes with a fit and predict/transform. This should make it clear that the instance isn't yet fit.
Fixes #12959
What does this implement/fix? Explain your changes.
The current error message that comes from use of a non-fitted RandomTreesEmbedding.transform doesn't help the user locate the problem. I've added a check_is_fitted() call just before the transform call to check if the fit has been performed and otherwise tell the user to do a fit first.
Any other comments?
This code and community is awesome.