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')
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')