The evaluation pages describes how submissions will be scored and how students should format their submissions. You don't need a sub-title at the top; the page title appears above. For an example of a high quality evaluation page, see the 2013 KDD Cup page, which we have included below:

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The evaluation metric for this competition is [Mean F1-Score](https://en.wikipedia.org/wiki/F-score). The F1 score, commonly used in information retrieval, measures accuracy using the statistics precision and recall.

Precision is the ratio of true positives to all predicted positives. Recall is the ratio of true positives to all actual positives. The F1 score is given by:

$$\text{F1} = 2\frac{\text{precision} \cdot \text{recall}}{\text{precision}+\text{recall}}\ \ \mathrm{where}\ \ \text{precision} = \frac{\text{true positives}}{\text{true positives}+\text{false positives}},\ \ \text{recall} = \frac{\text{true positives}}{\text{true positives}+\text{false negatives}}$$

The F1 metric weights recall and precision equally, and a good retrieval algorithm will maximize both precision and recall simultaneously. Thus, moderately good performance on both will be favored over extremely good performance on one and poor performance on the other.

## Submission Format

A valid submission file should contain two columns: "ID" and " Label". The "ID" column for the submission should match with "ID" column in the testing dataset provided. For each row, " Label" should correspond to your detection of the "Log" that corresponds to that "ID" in the provided test dataset. Take a look at sample_submissions.csv to understand better. Contact organizers through Unstop in case of any queries. 

IMPORTANT NOTE: In your csv file, the top row should be: ["ID", " Label"] and not ["ID", "Label"]. Notice the space before Label.