## Metric
This competition metric is `ROC AUC`(the measure of the ability of a classifier to distinguish between classes). Full form is Receiver Operating Characteristic, Area Under the Curve

Usually, it is used in classification tasks evaluations

## Submission Format
Submission files should contain two columns: `id` and `proba`
`id` should contain example's identificator, `proba` have to be a float number of the probability of a true label

All files should have a `.csv` extension with standard pandas csv saving options
Saving example is -
```
df.to_csv('submission.csv', index=False)
```

## Format example:
id,proba
1,0.16270209934189291
2,0.21975484280643935
3,0.17125674517466864
4,0.74107274730291206

in csv submission file.

Example of a submission file is presented in `Data` tab.