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"""
=============================
Recursive feature elimination
=============================
A recursive feature elimination example showing the relevance of pixels in
a digit classification task.
"""
print __doc__
from sklearn.svm import SVC
from sklearn.datasets import load_digits
from sklearn.feature_selection import RFE
# 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
import pylab as pl
pl.matshow(ranking)
pl.colorbar()
pl.title("Ranking of pixels with RFE")
pl.show()
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