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Recursive feature eliminationΒΆ

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

../_images/plot_rfe_digits_001.png

Python source code: plot_rfe_digits.py

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 matplotlib.pyplot as plt
plt.matshow(ranking)
plt.colorbar()
plt.title("Ranking of pixels with RFE")
plt.show()

Total running time of the example: 8.47 seconds ( 0 minutes 8.47 seconds)

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