DOC Fix docstring for class MissingIndicator
@@ -568,26 +568,26 @@ class MissingIndicator(TransformerMixin, BaseEstimator):
nullable integer dtypes with missing values, `missing_values`
should be set to `np.nan`, since `pd.NA` will be converted to `np.nan`.
- features : str, default=None
+ features : {'missing-only', 'all'}, default='missing-only'
Whether the imputer mask should represent all or a subset of
features.
- - If "missing-only" (default), the imputer mask will only represent
+ - If 'missing-only' (default), the imputer mask will only represent
features containing missing values during fit time.
- - If "all", the imputer mask will represent all features.
+ - If 'all', the imputer mask will represent all features.
- sparse : boolean or "auto", default=None
+ sparse : bool or 'auto', default='auto'
Whether the imputer mask format should be sparse or dense.
- - If "auto" (default), the imputer mask will be of same type as
+ - If 'auto' (default), the imputer mask will be of same type as
input.
- If True, the imputer mask will be a sparse matrix.
- If False, the imputer mask will be a numpy array.
- error_on_new : boolean, default=None
- If True (default), transform will raise an error when there are
- features with missing values in transform that have no missing values
- in fit. This is applicable only when ``features="missing-only"``.
+ error_on_new : bool, default=True
+ If True, transform will raise an error when there are features with
+ missing values in transform that have no missing values in fit. This is
+ applicable only when `features='missing-only'`.
Attributes
----------
