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from sklearn import datasetsfrom sklearn.tree import DecisionTreeClassifierfrom sklearn.model_selection import ShuffleSplit, cross_val_scoreX, y = datasets.load_iris(return_X_y=True)clf = DecisionTreeClassifier(random_state=42)ss = ShuffleSplit(train_size=0.6, test_size=0.3, n_splits = 5)scores = cross_val_score(clf, X, y, cv = ss)print("Cross Validation Scores: ", scores)print("Average CV Score: ", scores.mean())print("Number of CV Scores used in Average: ", len(scores)) Cross Validation Scores: [0.91111111 0.97777778 0.93333333 0.97777778 0.95555556] Average CV Score: 0.9511111111111111 Number of CV Scores used in Average: 5