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from sklearn import datasets from sklearn.model_selection import train_test_split from sklearn.metrics import accuracy_score from sklearn.tree import DecisionTreeClassifier data = datasets.load_wine() X = data.data y = data.target X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.25, random_state = 22) dtree = DecisionTreeClassifier(random_state = 22) dtree.fit(X_train,y_train) y_pred = dtree.predict(X_test) print("Train data accuracy:",accuracy_score(y_true = y_train, y_pred = dtree.predict(X_train))) print("Test data accuracy:",accuracy_score(y_true = y_test, y_pred = y_pred))
Train data accuracy: 1.0 Test data accuracy: 0.8222222222222222
