From 120ef1924c74bede7c531ccc0ce972961d761110 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=E6=B8=A1=E9=82=8A=20=E7=BE=8E=E5=B8=8C?= Date: Mon, 28 Aug 2023 14:45:19 +0900 Subject: [PATCH] DOC: Added dropdowns to 4.1 PDPs --- doc/modules/partial_dependence.rst | 6 ++++++ 1 file changed, 6 insertions(+) diff --git a/doc/modules/partial_dependence.rst b/doc/modules/partial_dependence.rst index 7ce099f2342e9..6fe5a79b51f63 100644 --- a/doc/modules/partial_dependence.rst +++ b/doc/modules/partial_dependence.rst @@ -79,6 +79,10 @@ parameter takes a list of indices, names of the categorical features or a boolea mask. The graphical representation of partial dependence for categorical features is a bar plot or a 2D heatmap. +|details-start| +**PDPs for multi-class classification** +|details-split| + For multi-class classification, you need to set the class label for which the PDPs should be created via the ``target`` argument:: @@ -93,6 +97,8 @@ the PDPs should be created via the ``target`` argument:: The same parameter ``target`` is used to specify the target in multi-output regression settings. +|details-end| + If you need the raw values of the partial dependence function rather than the plots, you can use the :func:`sklearn.inspection.partial_dependence` function::