.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "auto_examples\0_data\plot_5_feature_select.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_0_data_plot_5_feature_select.py>`
        to download the full example code or to run this example in your browser via Binder

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

.. _sphx_glr_auto_examples_0_data_plot_5_feature_select.py:


Feature Selection
=====================================

Four built-in feature selection strategies using the BikeSharing dataset as example.

.. GENERATED FROM PYTHON SOURCE LINES 10-11

Experiment initialization and data preparation

.. GENERATED FROM PYTHON SOURCE LINES 11-17

.. code-block:: default

    from piml import Experiment

    exp = Experiment()
    exp.data_loader(data="BikeSharing", silent=True)
    exp.data_prepare(target="cnt", task_type="regression", silent=True)








.. GENERATED FROM PYTHON SOURCE LINES 18-19

Feature selections using Pearson correlation strategy 

.. GENERATED FROM PYTHON SOURCE LINES 19-21

.. code-block:: default

    exp.feature_select(method="cor", corr_algorithm="pearson", threshold=0.1, figsize=(5, 4))




.. image-sg:: /auto_examples/0_data/images/sphx_glr_plot_5_feature_select_001.png
   :alt: Pearson Correlation (Top10)
   :srcset: /auto_examples/0_data/images/sphx_glr_plot_5_feature_select_001.png
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 22-23

Feature selections using Spearman correlation strategy 

.. GENERATED FROM PYTHON SOURCE LINES 23-25

.. code-block:: default

    exp.feature_select(method="cor", corr_algorithm="spearman", threshold=0.1, figsize=(5, 4))




.. image-sg:: /auto_examples/0_data/images/sphx_glr_plot_5_feature_select_002.png
   :alt: Spearman Correlation (Top10)
   :srcset: /auto_examples/0_data/images/sphx_glr_plot_5_feature_select_002.png
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 26-27

Feature selections using distance correlation strategy 

.. GENERATED FROM PYTHON SOURCE LINES 27-29

.. code-block:: default

    exp.feature_select(method="dcor", threshold=0.1, figsize=(5, 4))




.. image-sg:: /auto_examples/0_data/images/sphx_glr_plot_5_feature_select_003.png
   :alt: Distance Correlation (Top10)
   :srcset: /auto_examples/0_data/images/sphx_glr_plot_5_feature_select_003.png
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 30-31

Feature selection using permutation feature importance strategy 

.. GENERATED FROM PYTHON SOURCE LINES 31-33

.. code-block:: default

    exp.feature_select(method="pfi", threshold=0.95, figsize=(5, 4))




.. image-sg:: /auto_examples/0_data/images/sphx_glr_plot_5_feature_select_004.png
   :alt: XGB-based Feature Importance (Top10)
   :srcset: /auto_examples/0_data/images/sphx_glr_plot_5_feature_select_004.png
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 34-35

Feature selection using randomized conditional independence test strategy 

.. GENERATED FROM PYTHON SOURCE LINES 35-37

.. code-block:: default

    exp.feature_select(method="rcit", threshold=0.001, n_forward_phase=2, kernel_size=100, figsize=(5, 4))




.. image-sg:: /auto_examples/0_data/images/sphx_glr_plot_5_feature_select_005.png
   :alt: RCIT
   :srcset: /auto_examples/0_data/images/sphx_glr_plot_5_feature_select_005.png
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 38-39

Feature selection using randomized conditional independence test strategy, where the initial Markov boundary is non-empty

.. GENERATED FROM PYTHON SOURCE LINES 39-40

.. code-block:: default

    exp.feature_select(method="rcit", threshold=0.001, preset=["hr", "temp"], figsize=(5, 4))



.. image-sg:: /auto_examples/0_data/images/sphx_glr_plot_5_feature_select_006.png
   :alt: RCIT
   :srcset: /auto_examples/0_data/images/sphx_glr_plot_5_feature_select_006.png
   :class: sphx-glr-single-img






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

   **Total running time of the script:** ( 1 minutes  6.865 seconds)

**Estimated memory usage:**  973 MB


.. _sphx_glr_download_auto_examples_0_data_plot_5_feature_select.py:

.. only:: html

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


    .. container:: binder-badge

      .. image:: images/binder_badge_logo.svg
        :target: https://mybinder.org/v2/gh/selfexplainml/piml-toolbox/main?urlpath=lab/tree/./docs/_build/html/notebooks/auto_examples/0_data/plot_5_feature_select.ipynb
        :alt: Launch binder
        :width: 150 px



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

      :download:`Download Python source code: plot_5_feature_select.py <plot_5_feature_select.py>`

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

      :download:`Download Jupyter notebook: plot_5_feature_select.ipynb <plot_5_feature_select.ipynb>`


.. only:: html

 .. rst-class:: sphx-glr-signature

    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_