sklearn.feature_selection
.SelectorMixin¶
- class sklearn.feature_selection.SelectorMixin[source]¶
Transformer mixin that performs feature selection given a support mask
This mixin provides a feature selector implementation with
transform
andinverse_transform
functionality 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.
- __init__(*args, **kwargs)¶
- 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.
- 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
indices
is False, this is a boolean array of shape [# input features], in which an element is True iff its corresponding feature is selected for retention. Ifindices
is True, this is an integer array of shape [# output features] whose values are indices into the input feature vector.