:orphan:

.. _general_examples:

Example Gallery
===============

This gallery contains examples demonstrating the capabilities of scikit-bayes.
All examples use matplotlib for visualization and can be downloaded as Python
scripts or Jupyter notebooks.


MixedNB Examples
----------------

Examples demonstrating the Mixed Naive Bayes classifier for heterogeneous data.

.. include:: plot_gaussiannb_equivalence.py
   :start-line: 1
   :end-line: 13

.. include:: plot_categoricalnb_equivalence.py
   :start-line: 1
   :end-line: 13

.. include:: plot_bernoullinb_equivalence.py
   :start-line: 1
   :end-line: 13

.. include:: plot_mixednb_vs_pipeline.py
   :start-line: 1
   :end-line: 24


AnDE Examples
-------------

Averaged n-Dependence Estimators solving problems Naive Bayes cannot.

.. include:: plot_aode_xor.py
   :start-line: 1
   :end-line: 26

.. include:: plot_a2de_xor_3d.py
   :start-line: 1
   :end-line: 13

.. include:: plot_a2de_xor_slice.py
   :start-line: 1
   :end-line: 13

.. include:: plot_aode_mixed_demo.py
   :start-line: 1
   :end-line: 13


Benchmarks and Comparisons
--------------------------

Performance comparisons of different model variants.

.. include:: compare_ande_variants.py
   :start-line: 1
   :end-line: 19

.. include:: compare_ande_interpretability.py
   :start-line: 1
   :end-line: 13



.. raw:: html

    <div class="sphx-glr-thumbnails">

.. thumbnail-parent-div-open

.. raw:: html

    <div class="sphx-glr-thumbcontainer" tooltip="This example demonstrates that skbn.mixed_nb.MixedNB produces identical results to sklearn.naive_bayes.GaussianNB when all features are continuous (Gaussian).">

.. only:: html

  .. image:: /auto_examples/images/thumb/sphx_glr_01_plot_gaussiannb_equivalence_thumb.png
    :alt:

  :doc:`/auto_examples/01_plot_gaussiannb_equivalence`

.. raw:: html

      <div class="sphx-glr-thumbnail-title">MixedNB Equivalence with GaussianNB</div>
    </div>


.. raw:: html

    <div class="sphx-glr-thumbcontainer" tooltip="This example demonstrates the limitations of the independence assumption in Naive Bayes and how Averaged n-Dependence Estimators (AnDE) overcome them.">

.. only:: html

  .. image:: /auto_examples/images/thumb/sphx_glr_06_plot_aode_xor_thumb.png
    :alt:

  :doc:`/auto_examples/06_plot_aode_xor`

.. raw:: html

      <div class="sphx-glr-thumbnail-title">Solving the XOR Problem: AnDE vs Naive Bayes</div>
    </div>


.. raw:: html

    <div class="sphx-glr-thumbcontainer" tooltip="While 3D visualizations show the global structure, taking a 2D slice (fixing one feature) allows for a precise analysis of the decision boundary.">

.. only:: html

  .. image:: /auto_examples/images/thumb/sphx_glr_07_plot_a2de_xor_slice_thumb.png
    :alt:

  :doc:`/auto_examples/07_plot_a2de_xor_slice`

.. raw:: html

      <div class="sphx-glr-thumbnail-title">Analytic View: 2D Slice of the 3D XOR Problem</div>
    </div>


.. raw:: html

    <div class="sphx-glr-thumbcontainer" tooltip="This example demonstrates that skbn.mixed_nb.MixedNB produces identical results to sklearn.naive_bayes.BernoulliNB when all features are binary (Bernoulli).">

.. only:: html

  .. image:: /auto_examples/images/thumb/sphx_glr_02_plot_bernoullinb_equivalence_thumb.png
    :alt:

  :doc:`/auto_examples/02_plot_bernoullinb_equivalence`

.. raw:: html

      <div class="sphx-glr-thumbnail-title">MixedNB Equivalence with BernoulliNB</div>
    </div>


.. raw:: html

    <div class="sphx-glr-thumbcontainer" tooltip="This example demonstrates that skbn.mixed_nb.MixedNB produces identical results to sklearn.naive_bayes.CategoricalNB when all features are discrete (categorical).">

.. only:: html

  .. image:: /auto_examples/images/thumb/sphx_glr_03_plot_categoricalnb_equivalence_thumb.png
    :alt:

  :doc:`/auto_examples/03_plot_categoricalnb_equivalence`

.. raw:: html

      <div class="sphx-glr-thumbnail-title">MixedNB Equivalence with CategoricalNB</div>
    </div>


.. raw:: html

    <div class="sphx-glr-thumbcontainer" tooltip="To visualize the 3D decision boundaries clearly, we plot a dense cloud of points (voxels) colored by the predicted class probability.">

.. only:: html

  .. image:: /auto_examples/images/thumb/sphx_glr_08_plot_a2de_xor_3d_thumb.png
    :alt:

  :doc:`/auto_examples/08_plot_a2de_xor_3d`

.. raw:: html

      <div class="sphx-glr-thumbnail-title">3D Voxel-Cloud Visualization: XOR Structure</div>
    </div>


.. raw:: html

    <div class="sphx-glr-thumbcontainer" tooltip="This example demonstrates why AnDE shines with mixed data types (Continuous + Categorical) compared to Naive Bayes.">

.. only:: html

  .. image:: /auto_examples/images/thumb/sphx_glr_05_plot_aode_mixed_demo_thumb.png
    :alt:

  :doc:`/auto_examples/05_plot_aode_mixed_demo`

.. raw:: html

      <div class="sphx-glr-thumbnail-title">The Power of Mixed Data: Context-Dependent Logic</div>
    </div>


.. raw:: html

    <div class="sphx-glr-thumbcontainer" tooltip="This example demonstrates the &quot;Embedded Feature Selection&quot; capability of Hybrid AnDE models (ALR).">

.. only:: html

  .. image:: /auto_examples/images/thumb/sphx_glr_10_plot_compare_ande_interpretability_thumb.png
    :alt:

  :doc:`/auto_examples/10_plot_compare_ande_interpretability`

.. raw:: html

      <div class="sphx-glr-thumbnail-title">Interpreting ALR: Automatic Feature Selection via Weights</div>
    </div>


.. raw:: html

    <div class="sphx-glr-thumbcontainer" tooltip="This example compares three strategies for handling a dataset with mixed continuous (Gaussian) and discrete (Categorical) features.">

.. only:: html

  .. image:: /auto_examples/images/thumb/sphx_glr_04_plot_mixednb_vs_pipeline_thumb.png
    :alt:

  :doc:`/auto_examples/04_plot_mixednb_vs_pipeline`

.. raw:: html

      <div class="sphx-glr-thumbnail-title">Handling Mixed Data Types with MixedNB</div>
    </div>


.. raw:: html

    <div class="sphx-glr-thumbcontainer" tooltip="This experiment compares the full hierarchy of parameter granularity in ALR.">

.. only:: html

  .. image:: /auto_examples/images/thumb/sphx_glr_09_plot_compare_ande_variants_thumb.png
    :alt:

  :doc:`/auto_examples/09_plot_compare_ande_variants`

.. raw:: html

      <div class="sphx-glr-thumbnail-title">Data Efficiency & Complexity: Generative vs. Hybrid Levels (L1-L4)</div>
    </div>


.. thumbnail-parent-div-close

.. raw:: html

    </div>


.. toctree::
   :hidden:

   /auto_examples/01_plot_gaussiannb_equivalence
   /auto_examples/06_plot_aode_xor
   /auto_examples/07_plot_a2de_xor_slice
   /auto_examples/02_plot_bernoullinb_equivalence
   /auto_examples/03_plot_categoricalnb_equivalence
   /auto_examples/08_plot_a2de_xor_3d
   /auto_examples/05_plot_aode_mixed_demo
   /auto_examples/10_plot_compare_ande_interpretability
   /auto_examples/04_plot_mixednb_vs_pipeline
   /auto_examples/09_plot_compare_ande_variants


.. only:: html

  .. container:: sphx-glr-footer sphx-glr-footer-gallery

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

      :download:`Download all examples in Python source code: auto_examples_python.zip </auto_examples/auto_examples_python.zip>`

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

      :download:`Download all examples in Jupyter notebooks: auto_examples_jupyter.zip </auto_examples/auto_examples_jupyter.zip>`


.. only:: html

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

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