我是一名机器学习的初学者，正在通过Kaggle的泰坦尼克号问题进行学习。据我所知，我已经确保了各个指标是一致的，当然我不会将这个问题归咎于Python，而是自己。然而，我仍然找不到问题的源头，Spyder IDE也帮不上忙。

这是我的代码:

这是堆栈跟踪:

Traceback (most recent call last):  File "<ipython-input-3-73797c87986e>", line 1, in <module>    runfile('C:/Users/Omar/Downloads/Kaggle Competition/Titanic.py', wdir='C:/Users/Omar/Downloads/Kaggle Competition')  File "C:\Users\Omar\Anaconda3\lib\site-packages\spyder\utils\site\sitecustomize.py", line 705, in runfile    execfile(filename, namespace)  File "C:\Users\Omar\Anaconda3\lib\site-packages\spyder\utils\site\sitecustomize.py", line 102, in execfile    exec(compile(f.read(), filename, 'exec'), namespace)  File "C:/Users/Omar/Downloads/Kaggle Competition/Titanic.py", line 58, in <module>    print(accuracy_score(val_y, val_predictions))  File "C:\Users\Omar\Anaconda3\lib\site-packages\sklearn\metrics\classification.py", line 176, in accuracy_score    y_type, y_true, y_pred = _check_targets(y_true, y_pred)  File "C:\Users\Omar\Anaconda3\lib\site-packages\sklearn\metrics\classification.py", line 81, in _check_targets    "and {1} targets".format(type_true, type_pred))ValueError: Classification metrics can't handle a mix of binary and continuous targets

回答：

您正在尝试将回归算法（DecisionTreeRegressor）用于二元分类问题；如预期的那样，回归模型会给出连续的输出，而错误实际发生在accuracy_score这里:

File "C:/Users/Omar/Downloads/Kaggle Competition/Titanic.py", line 58, in <module>    print(accuracy_score(val_y, val_predictions)) 

它期望的是二元输出，因此出现了错误。

首先，请将您的模型更改为:

from sklearn.tree import DecisionTreeClassifiertitanic_model = DecisionTreeClassifier()