sklearn.feature_selection.SelectorMixin¶
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class
sklearn.feature_selection.SelectorMixin[source]¶ Transformer mixin that performs feature selection given a support mask
This mixin provides a feature selector implementation with
transformandinverse_transformfunctionality given an implementation of_get_support_mask.Methods
fit_transform(X[, y])Fit to data, then transform it.
get_support([indices])Get a mask, or integer index, of the features selected
Reverse the transformation operation
transform(X)Reduce X to the selected features.
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__init__(*args, **kwargs)¶ Initialize self. See help(type(self)) for accurate signature.
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fit_transform(X, y=None, **fit_params)[source]¶ Fit to data, then transform it.
Fits transformer to X and y with optional parameters fit_params and returns a transformed version of X.
- Parameters
- X{array-like, sparse matrix, dataframe} of shape (n_samples, n_features)
- yndarray of shape (n_samples,), default=None
Target values.
- **fit_paramsdict
Additional fit parameters.
- Returns
- X_newndarray array of shape (n_samples, n_features_new)
Transformed array.
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get_support(indices=False)[source]¶ Get a mask, or integer index, of the features selected
- Parameters
- indicesboolean (default False)
If True, the return value will be an array of integers, rather than a boolean mask.
- Returns
- supportarray
An index that selects the retained features from a feature vector. If
indicesis False, this is a boolean array of shape [# input features], in which an element is True iff its corresponding feature is selected for retention. Ifindicesis True, this is an integer array of shape [# output features] whose values are indices into the input feature vector.
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