This competition is about predicting person's bankrupcy. You'll have dataset with depersonalized values from one of the banks. Your aim is to predict is a person bankrupt or not.

The full dataset contains one thousand examples, and as always, splitted into `train` and `test` set with the size of 800 and 200 respectively.
This is a classification task and the purpose is to predict person's bankruptcy for the test set.

You'll have to provide your solution file, that contains predicted probabilities of bankruptcies. The probabilities are linked with id's of the examples, so there will be 2 columns in your solution files.

Shortly, metric is `ROC AUC`.

More about submission file format and competition metric is in `metric and submission ` tab on the left.

Dataset and variables description are presented in the `Data` tab.

Enjoy the participation!

> The hardest part of any deal is starting!