.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "auto_examples/approximators/plot_proxyshap.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_approximators_plot_proxyshap.py>`
        to download the full example code.

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

.. _sphx_glr_auto_examples_approximators_plot_proxyshap.py:


ProxySHAP
=========

Proxy model-based interaction approximation using
:class:`~shapiq.approximator.proxy.proxyshap.ProxySHAP`.

.. GENERATED FROM PYTHON SOURCE LINES 8-27

.. code-block:: Python


    from __future__ import annotations

    import numpy as np

    from shapiq.approximator import ProxySHAP

    N_PLAYERS = 8
    BUDGET = 200
    feature_names = [f"x{i}" for i in range(N_PLAYERS)]

    weights = np.array([0.4, 0.3, 0.2, 0.1, 0.05, -0.1, -0.2, -0.3])


    def game_fun(coalitions: np.ndarray) -> np.ndarray:
        coalitions = np.atleast_2d(coalitions)
        return (coalitions @ weights) + 0.5 * coalitions[:, 0] * coalitions[:, 1]









.. GENERATED FROM PYTHON SOURCE LINES 28-30

Approximate interaction values
------------------------------

.. GENERATED FROM PYTHON SOURCE LINES 30-35

.. code-block:: Python


    approximator = ProxySHAP(n=N_PLAYERS, max_order=2, random_state=42)
    iv = approximator.approximate(BUDGET, game_fun)
    print(iv)





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

 .. code-block:: none

    InteractionValues(
        index=k-SII, max_order=2, min_order=0, estimated=False, estimation_budget=200,
        n_players=8, baseline_value=0.0,
        Top 10 interactions:
            (0, 1): 0.5000328301043857
            (0,): 0.3964762858761372
            (1,): 0.30150235323516017
            (2,): 0.19489008459760143
            (3,): 0.0960914356173253
            (4,): 0.04864816098376976
            (1, 6): 0.0016383139535357531
            (5,): -0.09461236294665057
            (6,): -0.19591249660592078
            (7,): -0.2970823921436667
    )




.. GENERATED FROM PYTHON SOURCE LINES 36-38

Force plot
----------

.. GENERATED FROM PYTHON SOURCE LINES 38-41

.. code-block:: Python


    iv.plot_force(feature_names=feature_names)




.. image-sg:: /auto_examples/approximators/images/sphx_glr_plot_proxyshap_001.png
   :alt: plot proxyshap
   :srcset: /auto_examples/approximators/images/sphx_glr_plot_proxyshap_001.png
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 42-44

Network plot
------------

.. GENERATED FROM PYTHON SOURCE LINES 44-46

.. code-block:: Python


    iv.plot_network(feature_names=feature_names)



.. image-sg:: /auto_examples/approximators/images/sphx_glr_plot_proxyshap_002.png
   :alt: plot proxyshap
   :srcset: /auto_examples/approximators/images/sphx_glr_plot_proxyshap_002.png
   :class: sphx-glr-single-img






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

   **Total running time of the script:** (0 minutes 0.744 seconds)


.. _sphx_glr_download_auto_examples_approximators_plot_proxyshap.py:

.. only:: html

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

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

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

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

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

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

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