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from sklearn import datasetsfrom sklearn.tree import DecisionTreeClassifierfrom sklearn.model_selection import KFold, cross_val_scoreX, y = datasets.load_iris(return_X_y=True)clf = DecisionTreeClassifier(random_state=42)k_folds = KFold(n_splits = 5)scores = cross_val_score(clf, X, y, cv = k_folds)print("Cross Validation Scores: ", scores)print("Average CV Score: ", scores.mean())print("Number of CV Scores used in Average: ", len(scores))Cross Validation Scores: [1. 1. 0.83333333 0.93333333 0.8 ] Average CV Score: 0.9133333333333333 Number of CV Scores used in Average: 5