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

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

.. _sphx_glr_auto_examples_linear_model_plot_lasso_lars.py:


=====================
Lasso path using LARS
=====================

Computes Lasso Path along the regularization parameter using the LARS
algorithm on the diabetes dataset. Each color represents a different
feature of the coefficient vector, and this is displayed as a function
of the regularization parameter.





.. image:: /auto_examples/linear_model/images/sphx_glr_plot_lasso_lars_001.png
    :class: sphx-glr-single-img


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

 Out:

 .. code-block:: none

    Computing regularization path using the LARS ...
    .




|


.. code-block:: python

    print(__doc__)

    # Author: Fabian Pedregosa <fabian.pedregosa@inria.fr>
    #         Alexandre Gramfort <alexandre.gramfort@inria.fr>
    # License: BSD 3 clause

    import numpy as np
    import matplotlib.pyplot as plt

    from sklearn import linear_model
    from sklearn import datasets

    diabetes = datasets.load_diabetes()
    X = diabetes.data
    y = diabetes.target

    print("Computing regularization path using the LARS ...")
    _, _, coefs = linear_model.lars_path(X, y, method='lasso', verbose=True)

    xx = np.sum(np.abs(coefs.T), axis=1)
    xx /= xx[-1]

    plt.plot(xx, coefs.T)
    ymin, ymax = plt.ylim()
    plt.vlines(xx, ymin, ymax, linestyle='dashed')
    plt.xlabel('|coef| / max|coef|')
    plt.ylabel('Coefficients')
    plt.title('LASSO Path')
    plt.axis('tight')
    plt.show()

**Total running time of the script:** ( 0 minutes  0.025 seconds)


.. _sphx_glr_download_auto_examples_linear_model_plot_lasso_lars.py:


.. only :: html

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



  .. container:: sphx-glr-download

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



  .. container:: sphx-glr-download

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


.. only:: html

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

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