### Fit model data

I have a very naive question about the `find_fit`

model. ~~There is ~~Is there some way to choose the "best" one? For example, in this simple situation:

```
R = [[0,1],[4,2],[8,4],[12,8],[16,16],[20,32],[24,64],[28,128],[32,256]]
p = scatter_plot(R)
p.show()
model(x) = 2^(a*x)
find_fit(R,model)
```

It will return `a==0.25`

. But for choosing this model `2^(a*x)`

, of course, I already know the answer. If you choose something more generic that makes more sense like

```
model(x) = a^(b*x)
```

It will return `a == 1.1017945777232188, b == 1.7875622665869968`

. So I was wondering if there is a way to get the optimized model for it.
Many thanks.