code: from sklearn import tree
  from sklearn.datasets import load_wine
  from sklearn.model_selection import train_test_split
  from sklearn.metrics import classification_report
  
  wine = load_wine()
  data = wine.data
  target = wine.target
  X_train, X_test, Y_train, Y_test = train_test_split(data, target, test_size=0.2, random_state=0)
  clf = tree.DecisionTreeClassifier()
  clf = clf.fit(X_train, Y_train)
  
  # テストデータのラベルを予測
  Y_pred = clf.predict(X_test)
  
  # 各クラスの適合率と再現率を表示
  print (classification_report(Y_test, Y_pred, target_names=wine.target_names))
  
apis: sklearn.tree.DecisionTreeClassifier sklearn.model_selection.train_test_split sklearn.metrics.classification_report sklearn.datasets.load_wine