.. _example_decomposition_plot_faces_decomposition.py: ============================ Faces dataset decompositions ============================ This example applies to :ref:`olivetti_faces` different unsupervised matrix decomposition (dimension reduction) methods from the module :py:mod:`sklearn.decomposition` (see the documentation chapter :ref:`decompositions`) . .. rst-class:: horizontal * .. image:: images/plot_faces_decomposition_001.png :scale: 47 * .. image:: images/plot_faces_decomposition_002.png :scale: 47 * .. image:: images/plot_faces_decomposition_003.png :scale: 47 * .. image:: images/plot_faces_decomposition_004.png :scale: 47 * .. image:: images/plot_faces_decomposition_005.png :scale: 47 * .. image:: images/plot_faces_decomposition_006.png :scale: 47 * .. image:: images/plot_faces_decomposition_007.png :scale: 47 * .. image:: images/plot_faces_decomposition_008.png :scale: 47 * .. image:: images/plot_faces_decomposition_009.png :scale: 47 **Script output**:: Dataset consists of 400 faces Extracting the top 6 Eigenfaces - RandomizedPCA... done in 0.218s Extracting the top 6 Non-negative components - NMF... done in 1.333s Extracting the top 6 Independent components - FastICA... done in 2.482s Extracting the top 6 Sparse comp. - MiniBatchSparsePCA... done in 1.331s Extracting the top 6 MiniBatchDictionaryLearning... done in 1.633s Extracting the top 6 Cluster centers - MiniBatchKMeans... done in 0.235s Extracting the top 6 Factor Analysis components - FA... done in 0.411s **Python source code:** :download:`plot_faces_decomposition.py ` .. literalinclude:: plot_faces_decomposition.py :lines: 12- **Total running time of the example:** 10.90 seconds ( 0 minutes 10.90 seconds)