.. _sphx_glr_auto_examples_feature_selection_plot_rfe_digits.py:


=============================
Recursive feature elimination
=============================

A recursive feature elimination example showing the relevance of pixels in
a digit classification task.

.. note::

    See also :ref:`sphx_glr_auto_examples_feature_selection_plot_rfe_with_cross_validation.py`




.. image:: /auto_examples/feature_selection/images/sphx_glr_plot_rfe_digits_001.png
    :align: center





.. code-block:: python

    print(__doc__)

    from sklearn.svm import SVC
    from sklearn.datasets import load_digits
    from sklearn.feature_selection import RFE
    import matplotlib.pyplot as plt

    # Load the digits dataset
    digits = load_digits()
    X = digits.images.reshape((len(digits.images), -1))
    y = digits.target

    # Create the RFE object and rank each pixel
    svc = SVC(kernel="linear", C=1)
    rfe = RFE(estimator=svc, n_features_to_select=1, step=1)
    rfe.fit(X, y)
    ranking = rfe.ranking_.reshape(digits.images[0].shape)

    # Plot pixel ranking
    plt.matshow(ranking, cmap=plt.cm.Blues)
    plt.colorbar()
    plt.title("Ranking of pixels with RFE")
    plt.show()

**Total running time of the script:**
(0 minutes 4.802 seconds)



.. container:: sphx-glr-download

    **Download Python source code:** :download:`plot_rfe_digits.py <plot_rfe_digits.py>`


.. container:: sphx-glr-download

    **Download IPython notebook:** :download:`plot_rfe_digits.ipynb <plot_rfe_digits.ipynb>`