On 02/02/2013 08:55 PM, Noel Dawe wrote:
>
> In examples/ensemble/plot_adaboost_twoclass.py:
>
> > @@ -0,0 +1,100 @@
> > +"""
> > +==================
> > +Two-class AdaBoost
> > +==================
> > +
> > +This example fits an AdaBoosted decision stump on a non-linearly separable
> > +classification dataset composed of two "Gaussian quantiles" clusters
> > +(see :func:`sklearn.datasets.make_gaussian_quantiles`) and plots the decision
> > +boundary, class probabilities, and two-class decision scores.
>
> You're right. Showing both the class B probabilities and decision 
> score is redundant. The example now only shows the decision boundary 
> and scores.
>
>
Could you please also add a sentence on what one can see from this plot?
I am not sure I understand it.