sklearn.feature_selection.f_classif

sklearn.feature_selection.f_classif(X, y) [source]

Compute the ANOVA F-value for the provided sample.

Read more in the User Guide.

Parameters

X{array-like, sparse matrix} shape = [n_samples, n_features]

The set of regressors that will be tested sequentially.

yarray of shape(n_samples)

The data matrix.

Returns

Farray, shape = [n_features,]

The set of F values.

pvalarray, shape = [n_features,]

The set of p-values.

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