提交的預測結果將使用 ROC 曲線下面積 (AUC) 來評分，這是衡量二元分類模型性能的重要指標。AUC 值介於 0 到 1 之間，越接近 1 表示模型性能越好。


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Submissions are evaluated on [area under the ROC curve](http://en.wikipedia.org/wiki/Receiver_operating_characteristic) between the predicted probability and the observed target.


## Submission File
For each ID in the test set, you must predict a probability for the TARGET variable. The file should contain a header and have the following format:

    ID,TARGET
    2,0
    5,0
    6,0
    etc.