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

.. only:: html

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

        :ref:`Go to the end <sphx_glr_download_glr_examples_utils_plot_confusion_matrices.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_glr_examples_utils_plot_confusion_matrices.py:


=================================================
Plot confusion matrices  
=================================================

plots inline multiple confusion matrices from  selected models  

.. GENERATED FROM PYTHON SOURCE LINES 8-11

.. code-block:: Python

    # Author: L.Kouadio 
    # Licence: BSD-3-clause 








.. GENERATED FROM PYTHON SOURCE LINES 12-15

Plot Radial basis function from the SVM kernel machines, the logit and the 
randomforest  stored as premodels in `p` objects and plot their 
confusion matrices 

.. GENERATED FROM PYTHON SOURCE LINES 15-36

.. code-block:: Python


    # Import the required models and fetch 4 models 
    # derived from RBF SVM kernel machines 
    # for instance then plot the confusion metric 
    import matplotlib.pyplot as plt 
    plt.style.use ('classic')
    from watex.datasets import fetch_data
    from watex.exlib.sklearn import train_test_split 
    from watex.models.premodels import p
    from watex.utils.plotutils import plot_confusion_matrices 
    # split the  data . Note that fetch_data output X and y 
    X, Xt, y, yt  = train_test_split (* fetch_data ('bagoue analysed'), test_size =.25  )  
    # compose the models 
    # from RBF, and poly 
    models =[ p.SVM.rbf.best_estimator_,
             p.LogisticRegression.best_estimator_,
             p.RandomForest.best_estimator_ 
             ]
    print(models )
    # now fit all estimators 
    fitted_models = [model.fit(X, y) for model in models ]




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

 .. code-block:: none

    [SVC(C=2.0, coef0=0, degree=1, gamma=0.125), LogisticRegression(), RandomForestClassifier(criterion='entropy', max_depth=16, n_estimators=350)]




.. GENERATED FROM PYTHON SOURCE LINES 37-38

* Plot the confusions metrics with the selected estimators 

.. GENERATED FROM PYTHON SOURCE LINES 38-41

.. code-block:: Python

    plot_confusion_matrices(fitted_models , Xt, yt)





.. image-sg:: /glr_examples/utils/images/sphx_glr_plot_confusion_matrices_001.png
   :alt: SVC, LogisticRegression, RandomForestClassifier
   :srcset: /glr_examples/utils/images/sphx_glr_plot_confusion_matrices_001.png
   :class: sphx-glr-single-img





.. GENERATED FROM PYTHON SOURCE LINES 42-43

* Plot  using the yellowbrick packages 

.. GENERATED FROM PYTHON SOURCE LINES 43-44

.. code-block:: Python


    plot_confusion_matrices(fitted_models , Xt, yt, pkg ='yb')


.. rst-class:: sphx-glr-horizontal


    *

      .. image-sg:: /glr_examples/utils/images/sphx_glr_plot_confusion_matrices_002.png
         :alt: SVC Confusion Matrix, LogisticRegression Confusion Matrix, RandomForestClassifier Confusion Matrix
         :srcset: /glr_examples/utils/images/sphx_glr_plot_confusion_matrices_002.png
         :class: sphx-glr-multi-img

    *

      .. image-sg:: /glr_examples/utils/images/sphx_glr_plot_confusion_matrices_003.png
         :alt: plot confusion matrices
         :srcset: /glr_examples/utils/images/sphx_glr_plot_confusion_matrices_003.png
         :class: sphx-glr-multi-img

    *

      .. image-sg:: /glr_examples/utils/images/sphx_glr_plot_confusion_matrices_004.png
         :alt: plot confusion matrices
         :srcset: /glr_examples/utils/images/sphx_glr_plot_confusion_matrices_004.png
         :class: sphx-glr-multi-img

    *

      .. image-sg:: /glr_examples/utils/images/sphx_glr_plot_confusion_matrices_005.png
         :alt: plot confusion matrices
         :srcset: /glr_examples/utils/images/sphx_glr_plot_confusion_matrices_005.png
         :class: sphx-glr-multi-img


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

 .. code-block:: none

    /home/docs/checkouts/readthedocs.org/user_builds/watex/envs/0.3.2/lib/python3.10/site-packages/yellowbrick/classifier/base.py:232: YellowbrickWarning:

    could not determine class_counts_ from previously fitted classifier

    /home/docs/checkouts/readthedocs.org/user_builds/watex/envs/0.3.2/lib/python3.10/site-packages/yellowbrick/classifier/base.py:232: YellowbrickWarning:

    could not determine class_counts_ from previously fitted classifier

    /home/docs/checkouts/readthedocs.org/user_builds/watex/envs/0.3.2/lib/python3.10/site-packages/yellowbrick/classifier/base.py:232: YellowbrickWarning:

    could not determine class_counts_ from previously fitted classifier






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

   **Total running time of the script:** (0 minutes 1.711 seconds)


.. _sphx_glr_download_glr_examples_utils_plot_confusion_matrices.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/watex/watex/0.3.X?urlpath=lab/tree/notebooks/glr_examples/utils/plot_confusion_matrices.ipynb
        :alt: Launch binder
        :width: 150 px

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

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

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

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


.. only:: html

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

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