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SelectFwe — scikit-learn 1.7.0 documentation
input_features = None ) [source] # Mask feature names according to selected...array-like, then input_features must match feature_names_in_ if feature_names_in_...scikit-learn.org/stable/modules/generated/sklearn.feature_selection.SelectFwe.html -
7.1. Pipelines and composite estimators — sciki...
must be transformers (i.e. must have a transform...integer array, a slice, a boolean mask, or with a make_column_selector...scikit-learn.org/stable/modules/compose.html -
MinCovDet — scikit-learn 1.7.0 documentation
The parameter must be in the range (0, 1]. random_state...ndarray of shape (n_samples,) A mask of the observations that have...scikit-learn.org/stable/modules/generated/sklearn.covariance.MinCovDet.html -
glossary.rst.txt
and that we must be careful to make :term:`meta-estimators`...data. Intrinsically, the model must be usable for prediction after...scikit-learn.org/stable/_sources/glossary.rst.txt -
Tweedie regression on insurance claims — scikit...
GammaRegressor mask_train = df_train [ "ClaimAmount" ] > 0 mask_test =...X_train [ mask_train . values ], df_train . loc [ mask_train ,...scikit-learn.org/stable/auto_examples/linear_model/plot_tweedie_regression_insurance_claims.html -
SequentialFeatureSelector — scikit-learn 1.7.0 ...
dtype=bool The mask of selected features. See also...input_features = None ) [source] # Mask feature names according to selected...scikit-learn.org/stable/modules/generated/sklearn.feature_selection.SequentialFeatureSelector.html -
MissingIndicator — scikit-learn 1.7.0 documenta...
default=’missing-only’ Whether the imputer mask should represent all or a subset...'missing-only' (default), the imputer mask will only represent features...scikit-learn.org/stable/modules/generated/sklearn.impute.MissingIndicator.html -
7.4. Imputation of missing values — scikit-lear...
>>> mask_all = indicator . fit_transform ( X ) >>> mask_all array([[...Missing values encoded by 0 must be used with dense input. The...scikit-learn.org/stable/modules/impute.html -
HistGradientBoostingClassifier — scikit-learn 1...
Must be strictly greater than 1....reserved for missing values. Must be no larger than 255. categorical_features...scikit-learn.org/stable/modules/generated/sklearn.ensemble.HistGradientBoostingClassifier.html -
RFECV — scikit-learn 1.7.0 documentation
The support is the mask of selected features. Added...ndarray of shape (n_features,) The mask of selected features. See also...scikit-learn.org/stable/modules/generated/sklearn.feature_selection.RFECV.html