Hello,

I am working on the rossmann example.

I don’t understand why we need to use the log of sales in the model?

`yl = np.log(y)`

Why couldn’t we use directly the sales values?

Afterwards, we convert it back directly (using exp), without using log values :

```
def exp_rmspe(y_pred, targ):
targ = inv_y(targ)
pct_var = (targ - inv_y(y_pred))/targ
return math.sqrt((pct_var**2).mean())
```

Is there a specific reason?

My second question is that in the couse example, we can see overfitting (for instance after several rounds: [ 2. 0.00707 0.01088 0.09878] )

In the image classification lesson I had understood that we have to be careful to avoid validation loss being greater than test loss (because of dropping). Why in that case can we push the model with this kind of loss? Is it because structured data are less sensitive to overfitting?

Thanks in advance for your help