.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "glr_examples/utils/plot_model_confusion_matrix.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_model_confusion_matrix.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_model_confusion_matrix.py:


=================================================
Plot confusion matrix  
=================================================

plots a confusion matrix for a single classifier model.  

.. GENERATED FROM PYTHON SOURCE LINES 8-11

.. code-block:: Python

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








.. GENERATED FROM PYTHON SOURCE LINES 12-14

Import the required models and fetch a an Ababoost model 
 for instance then plot the confusion metric 

.. GENERATED FROM PYTHON SOURCE LINES 14-26

.. code-block:: Python

    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 import pModels 
    from watex.utils.plotutils import plot_confusion_matrix
    # 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  )  
    # train the model with the best estimator 
    pmo = pModels (model ='ada' ) 
    pmo.fit(X, y )
    print(pmo.estimator_ )




.. 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/sklearn/ensemble/_weight_boosting.py:519: FutureWarning:

    The SAMME.R algorithm (the default) is deprecated and will be removed in 1.6. Use the SAMME algorithm to circumvent this warning.

    AdaBoostClassifier(estimator=DecisionTreeClassifier(criterion='entropy',
                                                        max_depth=7),
                       learning_rate=0.06)




.. GENERATED FROM PYTHON SOURCE LINES 27-29

Predict the score using under the hood the best estimator 
for adaboost classifier 

.. GENERATED FROM PYTHON SOURCE LINES 29-34

.. code-block:: Python

    ypred = pmo.predict(Xt) 

    # now plot the score 
    plot_confusion_matrix (yt , ypred )




.. image-sg:: /glr_examples/utils/images/sphx_glr_plot_model_confusion_matrix_001.png
   :alt: plot model confusion matrix
   :srcset: /glr_examples/utils/images/sphx_glr_plot_model_confusion_matrix_001.png
   :class: sphx-glr-single-img


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

 .. code-block:: none


    array([[25,  4,  0,  1],
           [ 9, 16,  3,  2],
           [ 1,  0,  7,  4],
           [ 0,  1,  2, 11]])




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

   **Total running time of the script:** (0 minutes 0.323 seconds)


.. _sphx_glr_download_glr_examples_utils_plot_model_confusion_matrix.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_model_confusion_matrix.ipynb
        :alt: Launch binder
        :width: 150 px

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

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

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

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


.. only:: html

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

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