code_1.py

from sklearn.tree import Decision Tree Classifier # 导入决策树模型
dtc = Decision Tree Classifier()
dtc.fit(X_train, y_train)
dtc_acc = dtc.score(X_test, y_test)*100
y_pred = dtc.predict(X_test) # 预测心脏病结果
print("Decision Tree Test Accuracy {:.2f}%".format(dtc_acc))
print("决策树 预测准确率: {:.2f}%".format(dtc.score(X_test, y_test)*100))
print("决策树 预测F1分数: {:.2f}%".format(f1_score(y_test, y_pred)*100))
print('决策树 混淆矩阵:\n', confusion_matrix(y_pred, y_test))