sklearn.feature_selection.f_classif¶
- sklearn.feature_selection.f_classif(X, y)¶
Compute the Anova F-value for the provided sample
Parameters: X : {array-like, sparse matrix} shape = [n_samples, n_features]
The set of regressors that will tested sequentially.
y : array of shape(n_samples)
The data matrix.
Returns: F : array, shape = [n_features,]
The set of F values.
pval : array, shape = [n_features,]
The set of p-values.
