Hi Sole, You can use `apply` on the training `X` to get the leaf where the sample will fall in. Then a groupby should allow you to get the statistic that you want.
Cheers, -- Guillaume Lemaitre Scikit-learn @ Inria Foundation https://glemaitre.github.io/ > On 7 Mar 2023, at 15:53, Sole Galli via scikit-learn > <scikit-learn@python.org> wrote: > > Hello, > > I would like to obtain final intervals from the decision tree structure. I am > not interested in every node, just the limits that take a sample to a final > decision /leaf. > > For example, if the tree structure is this one: > |--- feature_0 <= 0.08 > | |--- class: 0 > |--- feature_0 > 0.08 > | |--- feature_0 <= 8.50 > | | |--- feature_0 <= 1.50 > | | | |--- class: 1 > | | |--- feature_0 > 1.50 > | | | |--- class: 1 > | |--- feature_0 > 8.50 > | | |--- feature_0 <= 60.25 > | | | |--- class: 0 > | | |--- feature_0 > 60.25 > | | | |--- class: 0 > Then, I would like to obtain these limits: > 0-0.08 ; 0.08-1.50; 1.50-8.50 ; 8.50-60; >60 > > Potentially as the following numpy array: > [-np.inf, 0.08, 1.5, 8.5, 60, np.inf] > > Is it possible? > > I have a stackoverflow question here for more details and code > https://stackoverflow.com/questions/75663472/how-to-obtain-the-interval-limits-from-a-decision-tree-with-scikit-learn > > Thank you! > Sole > > Sent with Proton Mail <https://proton.me/> secure email. > _______________________________________________ > 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
