def f_classif(X, y):
 (X, y) = check_X_y(X, y, ['csr', 'csc', 'coo'])
 args = [X[safe_mask(X, (y == k))] for k in np.unique(y)]
 return f_oneway(*args)

def f_classif ( X , y ) : ( X , y ) = check_X_y ( X , y , [ 'csr' , 'csc' , 'coo' ] ) args = [ X [ safe_mask ( X , ( y == k ) ) ] for k in np . unique ( y ) ] return f_oneway ( * args )
compute the anova f-value for the provided sample .