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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 validation
Cross-validation is a resampling procedure used to evaluate machine learning models on a limited data sample. The procedure has a single parameter called k that refers to the number of groups that a given data sample is to be split into. As such, the procedure is often called k-fold cross-validation.
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