The evaluation metric for this competition is AUC: the Area Under the ROC Curve  ([https://en.wikipedia.org/wiki/Receiver_operating_characteristic](url), [https://scikit-learn.org/stable/modules/model_evaluation.html#roc-metrics](url)). 

The Competition leaderboard has two parts. The public leaderboard provides publicly visible submission scores based on a representative sample of the test data. This leaderboard is visible throughout the competition. The private leaderboard, by contrast, tracks model performance using the remainder of the test data. The private leaderboard thus has final say on whose models are best, and hence, who the winners and losers of the Competition will be. Which subset of data is calculated on the private leaderboard or a submission’s performance on the private leaderboard is not released to users until the competition has been closed.
## Submission Format **For every molecule in the test dataset**, submission files should contain two columns: `Id` and `Predicted` which contains your label prediction of this row. See file `sample submission.csv` which is a submission with random predictions.