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

    Click :ref:`here <sphx_glr_download_packages_scikit-learn_auto_examples_plot_linear_model_cv.py>` to download the full example code
.. rst-class:: sphx-glr-example-title

.. _sphx_glr_packages_scikit-learn_auto_examples_plot_linear_model_cv.py:


================================================================
Use the RidgeCV and LassoCV to set the regularization parameter
================================================================




Load the diabetes dataset



.. code-block:: python

    from sklearn.datasets import load_diabetes
    data = load_diabetes()
    X, y = data.data, data.target
    print(X.shape)





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

 Out:

 .. code-block:: none

    (442, 10)


Compute the cross-validation score with the default hyper-parameters



.. code-block:: python

    from sklearn.model_selection import cross_val_score
    from sklearn.linear_model import Ridge, Lasso

    for Model in [Ridge, Lasso]:
        model = Model()
        print('%s: %s' % (Model.__name__,
                          cross_val_score(model, X, y).mean()))





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

 Out:

 .. code-block:: none

    Ridge: 0.4101758336587286
    Lasso: 0.3375597834274947


We compute the cross-validation score as a function of alpha, the
strength of the regularization for Lasso and Ridge



.. code-block:: python

    import numpy as np
    from matplotlib import pyplot as plt

    alphas = np.logspace(-3, -1, 30)

    plt.figure(figsize=(5, 3))

    for Model in [Lasso, Ridge]:
        scores = [cross_val_score(Model(alpha), X, y, cv=3).mean()
                for alpha in alphas]
        plt.plot(alphas, scores, label=Model.__name__)

    plt.legend(loc='lower left')
    plt.xlabel('alpha')
    plt.ylabel('cross validation score')
    plt.tight_layout()
    plt.show()



.. image:: /packages/scikit-learn/auto_examples/images/sphx_glr_plot_linear_model_cv_001.png
    :class: sphx-glr-single-img




**Total running time of the script:** ( 0 minutes  0.355 seconds)


.. _sphx_glr_download_packages_scikit-learn_auto_examples_plot_linear_model_cv.py:


.. only :: html

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



  .. container:: sphx-glr-download

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



  .. container:: sphx-glr-download

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


.. only:: html

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

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