Comments (10)
Yeah, that makes sense. In get_dummies
in one_hot we build up the encoded columns based on what is in the passed in X
, but really ought to get the categories from the pre-trained OrdinalEncoder
that got built in fit
. I think that would solve this issue.
Is the assumption that all categories you want to encode are present in the dataset you pass to fit
reasonable?
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Yes, @wdm0006 your assumption is correct, all categories to encode should be passed in the dataset to fit
.
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Are you interested in working on a PR @justkunz? If not I'll try to work on this soon.
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@wdm0006 I can get a quick PR up.
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Fixed by #20
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Will do a new release soon, would like to try to fix #18 beforehand though if possible.
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@wdm0006 what's the status of the 1.2.4 release?
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I need to do a docs update with some of the recent PRs, but will try to get it out this week.
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@justkunz, just released it.
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Thanks @wdm0006!
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Related Issues (20)
- Equivalent method to sklearn's partial_fit? HOT 1
- CountEncoder incorrectly counts Timestamp columns HOT 3
- Target encoding categories with a single training example HOT 1
- DOC: one of the source links is dead HOT 1
- Missing text in documentation HOT 2
- Support Pandas 2.1 HOT 1
- Feature Request: Count-Based Target Encoder (Dracula)? HOT 1
- Pandas' string columns are not recognized HOT 3
- Pandas copy-on-write doesn't work properly HOT 2
- pd.NA should behave as np.nan HOT 5
- Multidimensional/composite target encoding HOT 4
- FutureWarning: is_categorical_dtype is deprecated and will be removed in a future version. HOT 2
- Support for Spark HOT 1
- EOF Error Raised while Calling HashingEncoders function HOT 6
- why we combine this library with main sklearn ? HOT 1
- catboost encoder get different result with catboost HOT 8
- Combining with set_output can produce errors HOT 1
- AttributeError: 'DataFrame' object has no attribute 'unique' HOT 1
- [Question; need help; support request] Possible to join multiple CountEncoders after parallel (multiprocessing) fitting? HOT 1
- FutureWarning in ordinal encoder when downcasting objects HOT 2
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