sklearn.feature_selection.f_classif

sklearn.feature_selection.f_classif(X, y)

Compute the ANOVA F-value for the provided sample.

Read more in the User Guide.

Parameters:

X{array-like, sparse matrix} of shape (n_samples, n_features)

The set of regressors that will be tested sequentially.

yndarray of shape (n_samples,)

The target vector.

Returns:

f_statisticndarray of shape (n_features,)

F-statistic for each feature.

p_valuesndarray of shape (n_features,)

P-values associated with the F-statistic.

See also

chi2

Chi-squared stats of non-negative features for classification tasks.

f_regression

F-value between label/feature for regression tasks.

Examples using sklearn.feature_selection.f_classif

Pipeline ANOVA SVM

Pipeline ANOVA SVM

Univariate Feature Selection

Univariate Feature Selection

SVM-Anova: SVM with univariate feature selection

SVM-Anova: SVM with univariate feature selection