Or just running estimator.tree_.apply(X_train) and inferring from there. On 30 August 2016 at 13:22, Nelson Liu <nf...@uw.edu> wrote:
> estimator.tree_.value gives the constant prediction of the tree at each > node. Think of it as what the tree would output if that node was a leaf. > > I don't think we have a readily available way of checking the number of > training samples of each class in a given tree node. The closest thing > easily accessible is estimator.tree_.n_node_samples. Getting > finer-grained counts of the number of samples in each class would require > modifying the source code, I think. > > On Mon, Aug 29, 2016 at 8:06 PM Ibrahim Dalal via scikit-learn < > scikit-learn@python.org> wrote: > >> Hi, >> >> What does the estimator.tree_.value array represent? I looked up the >> source code but not able to get what it is. I am interested in the number >> of training samples of each class in a given tree node. >> >> Thanks >> >> On Mon, Aug 29, 2016 at 9:22 PM, Andreas Mueller <t3k...@gmail.com> >> wrote: >> >>> >>> >>> On 08/28/2016 03:23 PM, Nelson Liu wrote: >>> >>> That should be: >>> node indicator = estimator.tree_.decision_path(X_test) >>> >>> PR welcome :) >>> >>> Was there a reason not to make this a "plot" example? >>> Would it take too long? Not having run examples by CI is a pretty big >>> maintenance burden. >>> >>> _______________________________________________ >>> scikit-learn mailing list >>> scikit-learn@python.org >>> https://mail.python.org/mailman/listinfo/scikit-learn >>> >>> >> _______________________________________________ >> scikit-learn mailing list >> scikit-learn@python.org >> https://mail.python.org/mailman/listinfo/scikit-learn >> > > _______________________________________________ > scikit-learn mailing list > scikit-learn@python.org > https://mail.python.org/mailman/listinfo/scikit-learn > >
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