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} of shape (n_samples, n_features)
The set of regressors that will be tested sequentially.
- yarray-like 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
chi2Chi-squared stats of non-negative features for classification tasks.
f_regressionF-value between label/feature for regression tasks.
