cross validation python
# SVC: support vector classifier (one of the "built-in" classifiers in scikit-learn)
# X, y: array-like representing input and target variables
# X.shape = (N, num_of_features)
# y.shape = (N, 1) in case of classification problem
from sklearn.model_selection import cross_val_score
clf = svm.SVC(kernel='linear', C=1, random_state=42)
scores = cross_val_score(clf, X, y, cv=5) # 5-fold cross validationsklearn cross validation score
from sklearn.model_selection import cross_val_score
scores = cross_val_score(classifier_logreg, X_train, y_train, cv = 5, scoring='accuracy')
print('Cross-validation scores:{}'.format(scores))
print('Average cross-validation score: {}'.format(scores.mean()))Copyright © 2021 Codeinu
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