from sklearn import datasets

from sklearn.model_selection import train_test_split

from sklearn.metrics import accuracy_score

from sklearn.tree import DecisionTreeClassifier

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data = datasets.load_wine()

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X = data.data

y = data.target

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X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.25, random_state = 22)

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dtree = DecisionTreeClassifier(random_state = 22)

dtree.fit(X_train,y_train)

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y_pred = dtree.predict(X_test)

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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))

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