The evaluation metric for this competition is [AUC-ROC](https://en.wikipedia.org/wiki/Receiver_operating_characteristic) Score. The AUC-ROC Score is commonly used for classification tasks. It measures the degree or measure of separability between the classes. The ROC curve is plotted with TPR against the FPR where TPR is on the y-axis and FPR is on the x-axis.

TPR or True Positive Rate can be defined as (True Positives / (True Positives + False Negatives))
Similarly FPR, or False Positive Rate, can be defined as (False Positives / (False Positives + True Negatives))

AUC - ROC curve is a performance measurement for the classification problems at various threshold settings

# **Submission Format**

Every Submission file should have the the following format:


```
ID,Class/ASD
1,1
```
You can refer to the sample_submission.csv file to get an idea on how to frame the submission file.