# 12th place post-processing

```
raters = np.array([18, 18,  6,  6,  6,  6, 18, 18,  6,  6,  6,  6,  6,  6,  6,  6,  6, 6,  6,  3, 18, 18, 18, 18, 18, 90,  6,  6,  6, 18])
mins = np.min(all_preds,axis=0)
maxs = np.max(all_preds,axis=0)
all_preds = (all_preds - mins)/(maxs - mins)
all_preds =  np.round(raters*all_preds).astype(np.float)/raters
```
If you have time please try this on your submission, I'm really interested to know how much it can boost your own score.