.. _sphx_glr_auto_examples_cluster_plot_digits_agglomeration.py:


=========================================================
Feature agglomeration
=========================================================

These images how similar features are merged together using
feature agglomeration.



.. image:: /auto_examples/cluster/images/sphx_glr_plot_digits_agglomeration_001.png
    :align: center





.. code-block:: python

    print(__doc__)

    # Code source: Gaël Varoquaux
    # Modified for documentation by Jaques Grobler
    # License: BSD 3 clause

    import numpy as np
    import matplotlib.pyplot as plt

    from sklearn import datasets, cluster
    from sklearn.feature_extraction.image import grid_to_graph

    digits = datasets.load_digits()
    images = digits.images
    X = np.reshape(images, (len(images), -1))
    connectivity = grid_to_graph(*images[0].shape)

    agglo = cluster.FeatureAgglomeration(connectivity=connectivity,
                                         n_clusters=32)

    agglo.fit(X)
    X_reduced = agglo.transform(X)

    X_restored = agglo.inverse_transform(X_reduced)
    images_restored = np.reshape(X_restored, images.shape)
    plt.figure(1, figsize=(4, 3.5))
    plt.clf()
    plt.subplots_adjust(left=.01, right=.99, bottom=.01, top=.91)
    for i in range(4):
        plt.subplot(3, 4, i + 1)
        plt.imshow(images[i], cmap=plt.cm.gray, vmax=16, interpolation='nearest')
        plt.xticks(())
        plt.yticks(())
        if i == 1:
            plt.title('Original data')
        plt.subplot(3, 4, 4 + i + 1)
        plt.imshow(images_restored[i], cmap=plt.cm.gray, vmax=16,
                   interpolation='nearest')
        if i == 1:
            plt.title('Agglomerated data')
        plt.xticks(())
        plt.yticks(())

    plt.subplot(3, 4, 10)
    plt.imshow(np.reshape(agglo.labels_, images[0].shape),
               interpolation='nearest', cmap=plt.cm.spectral)
    plt.xticks(())
    plt.yticks(())
    plt.title('Labels')
    plt.show()

**Total running time of the script:**
(0 minutes 0.799 seconds)



.. container:: sphx-glr-download

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


.. container:: sphx-glr-download

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