osting:
`$$p(y=c|x) = \frac{e^{\hat{y}^{(c)}}}{\sum_{j=1}^k e^{\hat{y}^{(j)}}}$$`
One regression tree per class (per gradient step).
---
#GradientBoostingClassifier / HistGradientBoostingClassifier

.center[
![:scale 70%](images/grad_boost_depth2.png)
]
???
Here’s an illustration of what this might look like for
classification. This is basically the same thing going on.
I’m plotting the probabilities assigned by the model.

Here's a first estimator, which makes some mistakes here and
makes a bunch of mi