sklearn.feature_selection.SelectKBest¶
- class sklearn.feature_selection.SelectKBest(score_func=<function f_classif at 0x2fd4f50>, k=10)¶
Select features according to the k highest scores.
Parameters : score_func : callable
Function taking two arrays X and y, and returning a pair of arrays (scores, pvalues).
k : int or “all”, optional, default=10
Number of top features to select. The “all” option bypasses selection, for use in a parameter search.
Notes
Ties between features with equal scores will be broken in an unspecified way.
Attributes
scores_ array-like, shape=(n_features,) Scores of features. pvalues_ array-like, shape=(n_features,) p-values of feature scores. Methods
fit(X, y) Evaluate the score function on samples X with outputs y. fit_transform(X[, y]) Fit to data, then transform it. get_params([deep]) Get parameters for this estimator. get_support([indices]) Get a mask, or integer index, of the features selected inverse_transform(X) Reverse the transformation operation set_params(**params) Set the parameters of this estimator. transform(X) Reduce X to the selected features. - __init__(score_func=<function f_classif at 0x2fd4f50>, k=10)¶
- fit(X, y)¶
Evaluate the score function on samples X with outputs y.
Records and selects features according to their scores.
- fit_transform(X, y=None, **fit_params)¶
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 : numpy array of shape [n_samples, n_features]
Training set.
y : numpy array of shape [n_samples]
Target values.
Returns : X_new : numpy array of shape [n_samples, n_features_new]
Transformed array.
- get_params(deep=True)¶
Get parameters for this estimator.
Parameters : deep: boolean, optional :
If True, will return the parameters for this estimator and contained subobjects that are estimators.
Returns : params : mapping of string to any
Parameter names mapped to their values.
- get_support(indices=False)¶
Get a mask, or integer index, of the features selected
Parameters : indices : boolean (default False)
If True, the return value will be an array of integers, rather than a boolean mask.
Returns : support : array
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. If indices is True, this is an integer array of shape [# output features] whose values are indices into the input feature vector.
- inverse_transform(X)¶
Reverse the transformation operation
Parameters : X : array of shape [n_samples, n_selected_features]
The input samples.
Returns : X_r : array of shape [n_samples, n_original_features]
X with columns of zeros inserted where features would have been removed by transform.
- set_params(**params)¶
Set the parameters of this estimator.
The method works on simple estimators as well as on nested objects (such as pipelines). The former have parameters of the form <component>__<parameter> so that it’s possible to update each component of a nested object.
Returns : self :
- transform(X)¶
Reduce X to the selected features.
Parameters : X : array of shape [n_samples, n_features]
The input samples.
Returns : X_r : array of shape [n_samples, n_selected_features]
The input samples with only the selected features.