OneHotEncoder: expose categories detected for each feature during fit #1182
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@@ Coverage Diff @@
## main #1182 +/- ##
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Coverage 99.92% 99.92%
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Files 196 196
Lines 11710 11729 +19
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+ Hits 11701 11720 +19
Misses 9 9
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| METHODS_TO_CHECK = ComponentBaseMeta.METHODS_TO_CHECK + ['categories'] | ||
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| class OneHotEncoder(Transformer, metaclass=OneHotEncoderMeta): |
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I generalized BaseMeta so that we can add to the list of methods to check, for specific subclasses. Because in this case for one-hot encoder, if a user calls categories before fit, we want an error to get thrown.
It would be so cool if we found a way to roll this all up in a decorator... but I'm not sure how at the moment.
| self._encoder = None | ||
| super().__init__(parameters=parameters, | ||
| component_obj=None, | ||
| random_state=random_state) | ||
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| def _get_cat_cols(self, X): | ||
| @staticmethod |
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Unrelated change, why not :)
| @@ -72,24 +80,24 @@ def fit(self, X, y=None): | |||
| if not isinstance(X, pd.DataFrame): | |||
| X = pd.DataFrame(X) | |||
| X_t = X | |||
| cols_to_encode = self._get_cat_cols(X_t) | |||
| self._cols_to_encode = self._get_cat_cols(X_t) | |||
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We now save _cols_to_encode, so that in categories we can index into the sklearn encoder's category list correctly.
| property_orig = dct[attribute] | ||
| dct[attribute] = property(cls.check_for_fit(property_orig.__get__), | ||
| property_orig.__set__, | ||
| property_orig.__delattr__) |
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Building off @jeremyliweishih 's great code
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| METHODS_TO_CHECK = ComponentBaseMeta.METHODS_TO_CHECK + ['categories'] | ||
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| class OneHotEncoder(Transformer, metaclass=OneHotEncoderMeta): |
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Fix #1180
Added an API to the one-hot-encoder for accessing the list of categories associated with a given feature.
Also, generalized the
BaseMetaabstraction to support subclasses overriding the list of methods to be validated.Will retarget against main once #1179 is merged