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Decision tree with scikit-learn

Decision tree pipeline

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Imagine you work with the wine dataset. Your task is to make predictions for the test data. To complete the task, put the steps below in the correct order.

Put the items in the correct order

clf = DecisionTreeClassifier(); clf.fit(X_train, y_train); clf.predict(X_test)

X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.33, random_state = 34)

X, y = load_wine(return_X_y=True)

from sklearn.datasets import load_wine; from sklearn.tree import DecisionTreeClassifier

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