# Scoring Metric
Submissions are evaluated using the *Normalized Gini Coefficient.*

During scoring, observations are sorted from the largest to the smallest predictions. Predictions are only used for ordering observations; therefore, the relative magnitude of the predictions are not used during scoring. The scoring algorithm then compares the cumulative proportion of positive class observations to a theoretical uniform proportion.

The Gini Coefficient ranges from approximately 0 for random guessing, to approximately 0.5 for a perfect score. The theoretical maximum for the discrete calculation is (1 - frac_pos) / 2.

The Normalized Gini Coefficient adjusts the score by the theoretical maximum so that the maximum score is 1.

The code to calculate Normalized Gini Coefficient in a number of different languages can be found in this forum thread.

# Submission File
For each id in the test set, you must predict a probability of an insurance claim in the target column. The file should contain a header and have the following format:
```
id,target
0,0.1
1,0.9
2,1.0
etc.
```