The evaluation metric for this competition is [Categorization Accuracy](https://developers.google.com/machine-learning/crash-course/classification/accuracy). The Categorization Accuracy score, commonly used in multi-class classification, measures accuracy by calculating number of correct predictions divided by total number of predictions. The Categorization Accuracy score is given by:

![An image](https://latex.codecogs.com/gif.latex?%5Cdpi%7B150%7D%20%5Ctext%7BAccuracy%7D%20%3D%20%5Cfrac%7B%5Ctext%7BNumber%20of%20correct%20predictions%7D%7D%7B%5Ctext%7BTotal%20number%20of%20predictions%7D%7D)

## Submission Format

Submission files should contain two columns: **image** and **class\_id** (**image** should be a list of filenames and **class\_id** should be predicted label for each image

The file should contain a header and have the following format:

```
image,class_id
test_000000.jpg,1
test_000001.jpg,5
test_000002.jpg,4
```