Submissions for this competition are evaluated using [Mean F1-Score](https://en.wikipedia.org/wiki/F-score) between the predicted and expected answers.

F1 is calculated as follows: 
![F1 formula](https://inside-machinelearning.com/wp-content/uploads/2021/09/F1-Score.png)

Where:
![precision and recall formulas](https://miro.medium.com/max/888/1*7J08ekAwupLBegeUI8muHA.png)

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.

**NOTE:**
> - True Positive [TP]   = your prediction is 1, and the ground truth is also 1 - **you predicted a positive** and **that's true**!
- False Positive [FP]    = your prediction is 1, and the ground truth is 0 - **you predicted a positive**, and **that's false**.
- False Negative [FN] = your prediction is 0, and the ground truth is 1 - **you predicted a negative**, and **that's false**.

## Submission Format

**For every Order in the dataset**, submission files should contain two columns: `Order UID_` and `driver_id`. 
> `driver_id` is between 0 and 79 and represents a mapping with the real id of the drivers.

The file should contain a header and have the following format:
```
Order UID_, driver_id
11326944f24cef4fcaaae0e7c391e21efe3d4d7c01af817917c08b842bbfc53a, 0
ea02e4c2c2d7c08037a7ad5c3a0d783a1e9edb162200f4dd5c5d6f7b4c0d070d, 0
169aa82c0225bf6f449b1b20e0090fa5a581e2f58cc2a17d85a20a58922b36f2, 0
ef73a6526107fd80fd7f87c453798e5a3f02edd7c0bf09e4ec178424f3d315cd, 0
4f9b60444a55153059a07baa92bf1b80d3638b6c9f2d4ea5bcb8242327690c86, 0
3545c1b564366d0aa09f678578ee00da3db38fda37fdf8abc5a99f94fec07226, 0
c9eae2911e82989777188303c543521d18a16cd0f4527253ca7d2a6be759a029, 0
3ab4e58e675eda0f76fb299fc78b0dd0b94af60b3252ddf0cad83ee072fa69a6, 0
473512d0b28cc619202cc04893559777a048bf9eaa5479520db129d799db8302, 0

```