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

.. only:: html

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

        Click :ref:`here <sphx_glr_download_sklearn_ensae_course_plot_linear_regression.py>`
        to download the full example code

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

.. _sphx_glr_sklearn_ensae_course_plot_linear_regression.py:


Simple Linear Regression
========================

See `LinearRegression <http://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LinearRegression.html>`_.

.. GENERATED FROM PYTHON SOURCE LINES 7-43



.. image-sg:: /sklearn_ensae_course/images/sphx_glr_plot_linear_regression_001.png
   :alt: plot linear regression
   :srcset: /sklearn_ensae_course/images/sphx_glr_plot_linear_regression_001.png
   :class: sphx-glr-single-img





.. code-block:: default


    import numpy as np
    import matplotlib.pyplot as plt
    from sklearn.linear_model import LinearRegression


    def plot_linear_regression():
        a = 0.5
        b = 1.0

        # x from 0 to 10
        x = 30 * np.random.random(20)

        # y = a*x + b with noise
        y = a * x + b + np.random.normal(size=x.shape)

        # create a linear regression classifier
        clf = LinearRegression()
        clf.fit(x[:, None], y)

        # predict y from the data
        x_new = np.linspace(0, 30, 100)
        y_new = clf.predict(x_new[:, None])

        # plot the results
        ax = plt.axes()
        ax.scatter(x, y)
        ax.plot(x_new, y_new)

        ax.set_xlabel('x')
        ax.set_ylabel('y')

        ax.axis('tight')


    plot_linear_regression()


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

   **Total running time of the script:** ( 0 minutes  2.326 seconds)


.. _sphx_glr_download_sklearn_ensae_course_plot_linear_regression.py:

.. only:: html

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


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

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

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

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


.. only:: html

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

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