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[MRG] Add tree submodule attribute documentation #14339

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Jul 13, 2019
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[MRG] Add tree submodule attribute documentation #14339

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42 changes: 42 additions & 0 deletions sklearn/tree/tree.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1293,6 +1293,32 @@ class ExtraTreeClassifier(DecisionTreeClassifier):
Note that these weights will be multiplied with sample_weight (passed
through the fit method) if sample_weight is specified.

Attributes
----------
classes_ : array of shape = [n_classes] or a list of such arrays
The classes labels (single output problem),
or a list of arrays of class labels (multi-output problem).

max_features_ : int,
The inferred value of max_features.

n_classes_ : int or list
The number of classes (for single output problems),
or a list containing the number of classes for each
output (for multi-output problems).

n_features_ : int
The number of features when ``fit`` is performed.

n_outputs_ : int
The number of outputs when ``fit`` is performed.

tree_ : Tree object
The underlying Tree object. Please refer to
``help(sklearn.tree._tree.Tree)`` for attributes of Tree object and
:ref:`sphx_glr_auto_examples_tree_plot_unveil_tree_structure.py`
for basic usage of these attributes.

See also
--------
ExtraTreeRegressor, sklearn.ensemble.ExtraTreesClassifier,
Expand Down Expand Up @@ -1461,6 +1487,22 @@ class ExtraTreeRegressor(DecisionTreeRegressor):
Best nodes are defined as relative reduction in impurity.
If None then unlimited number of leaf nodes.

Attributes
----------
max_features_ : int,
The inferred value of max_features.

n_features_ : int
The number of features when ``fit`` is performed.

n_outputs_ : int
The number of outputs when ``fit`` is performed.

tree_ : Tree object
The underlying Tree object. Please refer to
``help(sklearn.tree._tree.Tree)`` for attributes of Tree object and
:ref:`sphx_glr_auto_examples_tree_plot_unveil_tree_structure.py`
for basic usage of these attributes.

See also
--------
Expand Down