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

.. only:: html

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

        :ref:`Go to the end <sphx_glr_download_packages_scikit-learn_auto_examples_plot_linear_regression.py>`
        to download the full example code

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

.. _sphx_glr_packages_scikit-learn_auto_examples_plot_linear_regression.py:


A simple linear regression
===========================

.. GENERATED FROM PYTHON SOURCE LINES 6-38



.. image-sg:: /packages/scikit-learn/auto_examples/images/sphx_glr_plot_linear_regression_001.png
   :alt: plot linear regression
   :srcset: /packages/scikit-learn/auto_examples/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

    # x from 0 to 30
    x = 30 * np.random.random((20, 1))

    # y = a*x + b with noise
    y = 0.5 * x + 1.0 + np.random.normal(size=x.shape)

    # create a linear regression model
    model = LinearRegression()
    model.fit(x, y)

    # predict y from the data
    x_new = np.linspace(0, 30, 100)
    y_new = model.predict(x_new[:, np.newaxis])

    # plot the results
    plt.figure(figsize=(4, 3))
    ax = plt.axes()
    ax.scatter(x, y)
    ax.plot(x_new, y_new)

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

    ax.axis('tight')


    plt.show()


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

   **Total running time of the script:** ( 0 minutes  0.048 seconds)


.. _sphx_glr_download_packages_scikit-learn_auto_examples_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>`_