.. _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 4.869 seconds) .. container:: sphx-glr-download **Download Python source code:** :download:`plot_rfe_digits.py ` .. container:: sphx-glr-download **Download IPython notebook:** :download:`plot_rfe_digits.ipynb `