The evaluation metric for this competition is AUC. The AUC is a commonly used evaluation metric for binary problems like this one. The interpretation is that given a random positive observation and negative observation, the AUC gives the proportion of the time you guess which is which correctly. It is less affected by sample balance than accuracy. A perfect model will score an AUC of 1, while random guessing will score an AUC of around of 0.5.
Submission Format
For every observation in the dataset, submission files should contain two columns: Id and Probability. The submission should be a csv file. The Id should just be the corresponding observation Id column from the dataset. The Probability column should be the predicted probability of the outcome 1 for that observation Id.

The file should contain a header and have the following format:.
The file should contain a header and have the following format:
Id,Probability
1,0.8