## Metric

This competition will evaluate your predictions using [ROC-AUC](https://scikit-learn.org/stable/modules/generated/sklearn.metrics.roc_auc_score.html). The predictions with the highest ROC-AUC score will earn first place on the Leaderboard.

## Submission Format

Your submission should be in the form of a csv file with two columns. 
1. `ID`
2. `prediction`

The `ID` column should be the `ID` column found in the predictors dataset.

**For example,** if I were to submit a csv of predictions where I predict the most common class for every observation, the first three rows of the submission would look like this:

| ID    | prediction  |
|-------|---------|
| 4359 |  0 |
| 7542  | 0 |
|  4777 | 0 |


***It is recommended that you save your predictions to csv using `pd.to_csv` (with  `index=False`) and that you import the saved file into a notebook, to make sure the data is structured as intended.***