.. _sphx_glr_auto_examples_decomposition: .. _decomposition_examples: Decomposition ------------- Examples concerning the :mod:`sklearn.decomposition` module. .. raw:: html <div class="sphx-glr-thumbnails"> .. raw:: html <div class="sphx-glr-thumbcontainer" tooltip="An example of estimating sources from noisy data."> .. only:: html .. image:: /auto_examples/decomposition/images/thumb/sphx_glr_plot_ica_blind_source_separation_thumb.png :alt: :ref:`sphx_glr_auto_examples_decomposition_plot_ica_blind_source_separation.py` .. raw:: html <div class="sphx-glr-thumbnail-title">Blind source separation using FastICA</div> </div> .. raw:: html <div class="sphx-glr-thumbcontainer" tooltip="The Iris dataset represents 3 kind of Iris flowers (Setosa, Versicolour and Virginica) with 4 a..."> .. only:: html .. image:: /auto_examples/decomposition/images/thumb/sphx_glr_plot_pca_vs_lda_thumb.png :alt: :ref:`sphx_glr_auto_examples_decomposition_plot_pca_vs_lda.py` .. raw:: html <div class="sphx-glr-thumbnail-title">Comparison of LDA and PCA 2D projection of Iris dataset</div> </div> .. raw:: html <div class="sphx-glr-thumbcontainer" tooltip="This example applies to olivetti_faces_dataset different unsupervised matrix decomposition (dim..."> .. only:: html .. image:: /auto_examples/decomposition/images/thumb/sphx_glr_plot_faces_decomposition_thumb.png :alt: :ref:`sphx_glr_auto_examples_decomposition_plot_faces_decomposition.py` .. raw:: html <div class="sphx-glr-thumbnail-title">Faces dataset decompositions</div> </div> .. raw:: html <div class="sphx-glr-thumbcontainer" tooltip="Investigating the Iris dataset, we see that sepal length, petal length and petal width are high..."> .. only:: html .. image:: /auto_examples/decomposition/images/thumb/sphx_glr_plot_varimax_fa_thumb.png :alt: :ref:`sphx_glr_auto_examples_decomposition_plot_varimax_fa.py` .. raw:: html <div class="sphx-glr-thumbnail-title">Factor Analysis (with rotation) to visualize patterns</div> </div> .. raw:: html <div class="sphx-glr-thumbcontainer" tooltip="This example illustrates visually in the feature space a comparison by results using two differ..."> .. only:: html .. image:: /auto_examples/decomposition/images/thumb/sphx_glr_plot_ica_vs_pca_thumb.png :alt: :ref:`sphx_glr_auto_examples_decomposition_plot_ica_vs_pca.py` .. raw:: html <div class="sphx-glr-thumbnail-title">FastICA on 2D point clouds</div> </div> .. raw:: html <div class="sphx-glr-thumbcontainer" tooltip="An example comparing the effect of reconstructing noisy fragments of a raccoon face image using..."> .. only:: html .. image:: /auto_examples/decomposition/images/thumb/sphx_glr_plot_image_denoising_thumb.png :alt: :ref:`sphx_glr_auto_examples_decomposition_plot_image_denoising.py` .. raw:: html <div class="sphx-glr-thumbnail-title">Image denoising using dictionary learning</div> </div> .. raw:: html <div class="sphx-glr-thumbcontainer" tooltip="Incremental principal component analysis (IPCA) is typically used as a replacement for principa..."> .. only:: html .. image:: /auto_examples/decomposition/images/thumb/sphx_glr_plot_incremental_pca_thumb.png :alt: :ref:`sphx_glr_auto_examples_decomposition_plot_incremental_pca.py` .. raw:: html <div class="sphx-glr-thumbnail-title">Incremental PCA</div> </div> .. raw:: html <div class="sphx-glr-thumbcontainer" tooltip="This example shows the difference between the Principal Components Analysis (~sklearn.decomposi..."> .. only:: html .. image:: /auto_examples/decomposition/images/thumb/sphx_glr_plot_kernel_pca_thumb.png :alt: :ref:`sphx_glr_auto_examples_decomposition_plot_kernel_pca.py` .. raw:: html <div class="sphx-glr-thumbnail-title">Kernel PCA</div> </div> .. raw:: html <div class="sphx-glr-thumbcontainer" tooltip="Probabilistic PCA and Factor Analysis are probabilistic models. The consequence is that the lik..."> .. only:: html .. image:: /auto_examples/decomposition/images/thumb/sphx_glr_plot_pca_vs_fa_model_selection_thumb.png :alt: :ref:`sphx_glr_auto_examples_decomposition_plot_pca_vs_fa_model_selection.py` .. raw:: html <div class="sphx-glr-thumbnail-title">Model selection with Probabilistic PCA and Factor Analysis (FA)</div> </div> .. raw:: html <div class="sphx-glr-thumbcontainer" tooltip="Principal Component Analysis applied to the Iris dataset."> .. only:: html .. image:: /auto_examples/decomposition/images/thumb/sphx_glr_plot_pca_iris_thumb.png :alt: :ref:`sphx_glr_auto_examples_decomposition_plot_pca_iris.py` .. raw:: html <div class="sphx-glr-thumbnail-title">PCA example with Iris Data-set</div> </div> .. raw:: html <div class="sphx-glr-thumbcontainer" tooltip="These figures aid in illustrating how a point cloud can be very flat in one direction--which is..."> .. only:: html .. image:: /auto_examples/decomposition/images/thumb/sphx_glr_plot_pca_3d_thumb.png :alt: :ref:`sphx_glr_auto_examples_decomposition_plot_pca_3d.py` .. raw:: html <div class="sphx-glr-thumbnail-title">Principal components analysis (PCA)</div> </div> .. raw:: html <div class="sphx-glr-thumbcontainer" tooltip="Transform a signal as a sparse combination of Ricker wavelets. This example visually compares d..."> .. only:: html .. image:: /auto_examples/decomposition/images/thumb/sphx_glr_plot_sparse_coding_thumb.png :alt: :ref:`sphx_glr_auto_examples_decomposition_plot_sparse_coding.py` .. raw:: html <div class="sphx-glr-thumbnail-title">Sparse coding with a precomputed dictionary</div> </div> .. raw:: html </div> .. toctree:: :hidden: /auto_examples/decomposition/plot_ica_blind_source_separation /auto_examples/decomposition/plot_pca_vs_lda /auto_examples/decomposition/plot_faces_decomposition /auto_examples/decomposition/plot_varimax_fa /auto_examples/decomposition/plot_ica_vs_pca /auto_examples/decomposition/plot_image_denoising /auto_examples/decomposition/plot_incremental_pca /auto_examples/decomposition/plot_kernel_pca /auto_examples/decomposition/plot_pca_vs_fa_model_selection /auto_examples/decomposition/plot_pca_iris /auto_examples/decomposition/plot_pca_3d /auto_examples/decomposition/plot_sparse_coding