sklearn cross_val_score scoring metric
from sklearn.linear_model import RidgeClassifier from sklearn.model_selection import cross_val_score clf = RidgeClassifier() # estimator score = cross_val_score(clf, X, y, cv=5) # By default, the score computed at each CV iteration is the score # method of the estimator. It is possible to change this by using # the scoring parameter: scores = cross_val_score(clf, X, y, cv=5, scoring='f1_macro')
Source: scikit-learn.org