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
chi2Chi-squared stats of non-negative features for classification tasks.
f_regressionF-value between label/feature for regression tasks.
