Pushing the docs to dev/ for branch: main, commit 3ccb9eb69581aa4a5091d2f10e8daebfca2b5633

Author: sklearn-ci

dev/.buildinfo

@@ -1,4 +1,4 @@
 # Sphinx build info version 1
 # This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
-config: 22c4d9890d4705af882ec206798422e7
+config: 3ff7ed7d47be4c10709fa1b833df92dd
 tags: 645f666f9bcd5a90fca523b33c5a78b7

dev/_downloads/07fcc19ba03226cd3d83d4e40ec44385/auto_examples_python.zip

@@ -44,14 +44,15 @@
 #
 # The decision classifier has an attribute called ``tree_`` which allows access
 # to low level attributes such as ``node_count``, the total number of nodes,
-# and ``max_depth``, the maximal depth of the tree. The tree_.compute_node_depths()
-# method computes the depth of each node in the tree. `tree_` also stores the
-# entire binary tree structure, represented as a number of parallel arrays. The
-# i-th element of each array holds information about the node ``i``. Node 0 is
-# the tree's root. Some of the arrays only apply to either leaves or split
-# nodes. In this case the values of the nodes of the other type is arbitrary.
-# For example, the arrays ``feature`` and ``threshold`` only apply to split
-# nodes. The values for leaf nodes in these arrays are therefore arbitrary.
+# and ``max_depth``, the maximal depth of the tree. The
+# ``tree_.compute_node_depths()`` method computes the depth of each node in the
+# tree. `tree_` also stores the entire binary tree structure, represented as a
+# number of parallel arrays. The i-th element of each array holds information
+# about the node ``i``. Node 0 is the tree's root. Some of the arrays only
+# apply to either leaves or split nodes. In this case the values of the nodes
+# of the other type is arbitrary. For example, the arrays ``feature`` and
+# ``threshold`` only apply to split nodes. The values for leaf nodes in these
+# arrays are therefore arbitrary.
 #
 # Among these arrays, we have:
 #