.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "auto_examples/trees/plot_treeshapiq_custom_tree.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

    .. note::
        :class: sphx-glr-download-link-note

        :ref:`Go to the end <sphx_glr_download_auto_examples_trees_plot_treeshapiq_custom_tree.py>`
        to download the full example code.

.. rst-class:: sphx-glr-example-title

.. _sphx_glr_auto_examples_trees_plot_treeshapiq_custom_tree.py:


TreeSHAP-IQ for Custom Tree Models
===================================

This example demonstrates how to use :class:`~shapiq.TreeExplainer` to explain
a custom tree model built from scratch using the Play Tennis dataset.

.. GENERATED FROM PYTHON SOURCE LINES 8-15

.. code-block:: Python


    from __future__ import annotations

    import numpy as np

    import shapiq








.. GENERATED FROM PYTHON SOURCE LINES 16-20

The Play Tennis Dataset
-----------------------
A classic dataset with 4 features (Outlook, Temperature, Humidity, Wind)
and a binary target (Play Tennis: Yes/No). Features are numerically encoded.

.. GENERATED FROM PYTHON SOURCE LINES 20-41

.. code-block:: Python


    X = np.array(
        [
            [1, 1, 1, 1],
            [1, 1, 1, 2],
            [2, 1, 1, 1],
            [3, 2, 1, 1],
            [3, 3, 2, 1],
            [3, 3, 2, 2],
            [2, 3, 2, 2],
            [1, 2, 1, 1],
            [1, 3, 2, 1],
            [3, 2, 2, 1],
            [1, 2, 2, 2],
            [2, 2, 1, 2],
            [2, 1, 2, 1],
            [3, 2, 1, 2],
        ]
    )
    y = np.array([0, 0, 1, 1, 1, 0, 1, 0, 1, 1, 1, 1, 1, 0])








.. GENERATED FROM PYTHON SOURCE LINES 42-55

Define a Custom Tree Model
---------------------------
We define a 3-node decision tree:

.. code-block:: text

        #0: Outlook
        /         \
       #1: 0      #2: Humidity
                  /           \
                 #3: 0        #4: Wind
                             /        \
                            #5: 0     #6: 1

.. GENERATED FROM PYTHON SOURCE LINES 55-66

.. code-block:: Python


    tree = shapiq.tree.TreeModel(
        children_left=np.array([1, -1, 3, -1, 5, -1, -1]),
        children_right=np.array([2, -1, 4, -1, 6, -1, -1]),
        children_missing=np.array([-1, -1, -1, -1, -1, -1, -1]),
        features=np.array([0, -2, 2, -2, 3, -2, -2]),
        thresholds=np.array([2.5, -2, 1.5, -2, 1.5, -2, -2]),
        values=np.array([0.5, 0.0, 0.5, 0.0, 0.0, 0.0, 1.0]),
        node_sample_weight=np.array([14, 5, 9, 5, 4, 1, 3]),
    )








.. GENERATED FROM PYTHON SOURCE LINES 67-70

Explain with TreeSHAP-IQ
-------------------------
Compute exact Shapley values for a single instance.

.. GENERATED FROM PYTHON SOURCE LINES 70-75

.. code-block:: Python


    explainer = shapiq.TreeExplainer(model=tree, index="SV", max_order=1)
    sv = explainer.explain(X[5])
    print(sv)
    sv.plot_force(feature_names=["Outlook", "Temperature", "Humidity", "Wind"])



.. image-sg:: /auto_examples/trees/images/sphx_glr_plot_treeshapiq_custom_tree_001.png
   :alt: plot treeshapiq custom tree
   :srcset: /auto_examples/trees/images/sphx_glr_plot_treeshapiq_custom_tree_001.png
   :class: sphx-glr-single-img


.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    InteractionValues(
        index=SV, max_order=1, min_order=0, estimated=True, estimation_budget=None,
        n_players=4, baseline_value=0.21428571428571427,
        Top 10 interactions:
            (2,): 0.40343915343915326
            (0,): 0.22982804232804221
            (): 0.21428571428571427
            (3,): 0.1524470899470899
            (1,): 0.0
    )





.. rst-class:: sphx-glr-timing

   **Total running time of the script:** (0 minutes 0.123 seconds)


.. _sphx_glr_download_auto_examples_trees_plot_treeshapiq_custom_tree.py:

.. only:: html

  .. container:: sphx-glr-footer sphx-glr-footer-example

    .. container:: sphx-glr-download sphx-glr-download-jupyter

      :download:`Download Jupyter notebook: plot_treeshapiq_custom_tree.ipynb <plot_treeshapiq_custom_tree.ipynb>`

    .. container:: sphx-glr-download sphx-glr-download-python

      :download:`Download Python source code: plot_treeshapiq_custom_tree.py <plot_treeshapiq_custom_tree.py>`

    .. container:: sphx-glr-download sphx-glr-download-zip

      :download:`Download zipped: plot_treeshapiq_custom_tree.zip <plot_treeshapiq_custom_tree.zip>`