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


=====================================================
Plot Stochastic Linear Adaptative Neuron Classifier  
=====================================================

visualizes the mini-batch by applying batch gradient descent to a 
smaller subset of test data.

.. GENERATED FROM PYTHON SOURCE LINES 9-12

.. code-block:: default

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








.. GENERATED FROM PYTHON SOURCE LINES 13-14

fetch data and uses the preprocessed  

.. GENERATED FROM PYTHON SOURCE LINES 14-29

.. code-block:: default

    import matplotlib.pyplot as plt 
    from watex.base import AdalineStochasticGradientDescent 
    from watex.analysis import decision_region 
    from watex.datasets import fetch_data 
    X, y = fetch_data ('bagoue prepared data') 

    fig, axe = plt.subplots (1, 2)
    asgd= AdalineStochasticGradientDescent (n_iter=15, eta=.01).fit(X.toarray(), y )
    decision_region(X.toarray(), y, clf=asgd, return_axe=True, axe= axe[0]) # test set view
    axe[0].set_title ("Adaline - Stochastic Gradient descent")

    axe[1].plot(range (1, len(asgd.cost_) +1 ), asgd.cost_, marker ="o")
    axe[1].set_xlabel ("Epochs")
    axe[1].set_ylabel ("Sum-squared-error")
    plt.tight_layout()
    plt.show() 


.. image-sg:: /glr_examples/base/images/sphx_glr_plot_ada_stochastic_gd_001.png
   :alt: Adaline - Stochastic Gradient descent
   :srcset: /glr_examples/base/images/sphx_glr_plot_ada_stochastic_gd_001.png
   :class: sphx-glr-single-img


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

 .. code-block:: none

    /home/docs/checkouts/readthedocs.org/user_builds/watex/checkouts/0.2.4/watex/analysis/decomposition.py:256: UserWarning:

    You passed a edgecolor/edgecolors ('black') for an unfilled marker ('x').  Matplotlib is ignoring the edgecolor in favor of the facecolor.  This behavior may change in the future.






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

   **Total running time of the script:** ( 0 minutes  0.412 seconds)


.. _sphx_glr_download_glr_examples_base_plot_ada_stochastic_gd.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/master?urlpath=lab/tree/notebooks/glr_examples/base/plot_ada_stochastic_gd.ipynb
        :alt: Launch binder
        :width: 150 px



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

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

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

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


.. only:: html

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

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