matplotlib怎么在一张图上画多条曲线？

问题：

# 如何让函数画在同一张画布上？
for i in range(1,15,3):
    train_score = []
    test_score = []
    for j in range(1,15,1):
        # 一步步找到各个参数的最优值
        DTree_classifier = DecisionTreeClassifier(max_depth=i,min_samples_leaf=j)
        # 训练数据
        DTree_classifier.fit(X_train, y_train)
        # 计算预测准确率
        train_s = accuracy_score(DTree_classifier.predict(X_train),y_train)
        train_score.append(train_s)
        test_s = accuracy_score(DTree_classifier.predict(X_test),y_test)
        test_score.append(test_s)
    
    plt.plot(train_score,label='Train_max_depth=%d'% i) 
    plt.plot(test_score,label='Test_max_depth=%d'% i) 
    plt.xlabel('min_samples_leaf')
    plt.ylabel('准确率')
    plt.legend()
    plt.grid()

结果：

如何将函数绘制在一张图上？

将循环里的plt.show()注释掉

plt.figure(figsize=(10,6))
for i in range(1,15,3):
    train_score = []
    test_score = []
    for j in range(1,15,1):
        # 一步步找到各个参数的最优值，这样不科学
        DTree_classifier = DecisionTreeClassifier(max_depth=i,min_samples_leaf=j)
        # 训练数据
        DTree_classifier.fit(X_train, y_train)
        # 计算预测准确率
        train_s = accuracy_score(DTree_classifier.predict(X_train),y_train)
        train_score.append(train_s)
        test_s = accuracy_score(DTree_classifier.predict(X_test),y_test)
        test_score.append(test_s)
    
    plt.plot(train_score,label='Train_max_depth=%d'% i) 
    plt.plot(test_score,label='Test_max_depth=%d'% i) 
    plt.xlabel('min_samples_leaf')
    plt.ylabel('准确率')
    plt.legend()
    plt.grid()
#     plt.show()

结果：

✌ Perfect~ ✌