.. _sphx_glr_auto_examples_decomposition:

.. _decomposition_examples:

Decomposition
-------------

Examples concerning the :mod:`sklearn.decomposition` module.




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    <div class="sphx-glr-thumbnails">


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    <div class="sphx-glr-thumbcontainer" tooltip="An example of estimating sources from noisy data.">

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  .. 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`

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      <div class="sphx-glr-thumbnail-title">Blind source separation using FastICA</div>
    </div>


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    <div class="sphx-glr-thumbcontainer" tooltip="The Iris dataset represents 3 kind of Iris flowers (Setosa, Versicolour and Virginica) with 4 a...">

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  .. 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`

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      <div class="sphx-glr-thumbnail-title">Comparison of LDA and PCA 2D projection of Iris dataset</div>
    </div>


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    <div class="sphx-glr-thumbcontainer" tooltip="This example applies to olivetti_faces_dataset different unsupervised matrix decomposition (dim...">

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  .. image:: /auto_examples/decomposition/images/thumb/sphx_glr_plot_faces_decomposition_thumb.png
    :alt:

  :ref:`sphx_glr_auto_examples_decomposition_plot_faces_decomposition.py`

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      <div class="sphx-glr-thumbnail-title">Faces dataset decompositions</div>
    </div>


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    <div class="sphx-glr-thumbcontainer" tooltip="Investigating the Iris dataset, we see that sepal length, petal length and petal width are high...">

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  .. image:: /auto_examples/decomposition/images/thumb/sphx_glr_plot_varimax_fa_thumb.png
    :alt:

  :ref:`sphx_glr_auto_examples_decomposition_plot_varimax_fa.py`

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      <div class="sphx-glr-thumbnail-title">Factor Analysis (with rotation) to visualize patterns</div>
    </div>


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    <div class="sphx-glr-thumbcontainer" tooltip="This example illustrates visually in the feature space a comparison by results using two differ...">

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  .. 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`

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      <div class="sphx-glr-thumbnail-title">FastICA on 2D point clouds</div>
    </div>


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    <div class="sphx-glr-thumbcontainer" tooltip="An example comparing the effect of reconstructing noisy fragments of a raccoon face image using...">

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  .. image:: /auto_examples/decomposition/images/thumb/sphx_glr_plot_image_denoising_thumb.png
    :alt:

  :ref:`sphx_glr_auto_examples_decomposition_plot_image_denoising.py`

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      <div class="sphx-glr-thumbnail-title">Image denoising using dictionary learning</div>
    </div>


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    <div class="sphx-glr-thumbcontainer" tooltip="Incremental principal component analysis (IPCA) is typically used as a replacement for principa...">

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  .. image:: /auto_examples/decomposition/images/thumb/sphx_glr_plot_incremental_pca_thumb.png
    :alt:

  :ref:`sphx_glr_auto_examples_decomposition_plot_incremental_pca.py`

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      <div class="sphx-glr-thumbnail-title">Incremental PCA</div>
    </div>


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    <div class="sphx-glr-thumbcontainer" tooltip="This example shows the difference between the Principal Components Analysis (~sklearn.decomposi...">

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  .. image:: /auto_examples/decomposition/images/thumb/sphx_glr_plot_kernel_pca_thumb.png
    :alt:

  :ref:`sphx_glr_auto_examples_decomposition_plot_kernel_pca.py`

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      <div class="sphx-glr-thumbnail-title">Kernel PCA</div>
    </div>


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    <div class="sphx-glr-thumbcontainer" tooltip="Probabilistic PCA and Factor Analysis are probabilistic models. The consequence is that the lik...">

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  .. 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`

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      <div class="sphx-glr-thumbnail-title">Model selection with Probabilistic PCA and Factor Analysis (FA)</div>
    </div>


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    <div class="sphx-glr-thumbcontainer" tooltip="Principal Component Analysis applied to the Iris dataset.">

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  .. image:: /auto_examples/decomposition/images/thumb/sphx_glr_plot_pca_iris_thumb.png
    :alt:

  :ref:`sphx_glr_auto_examples_decomposition_plot_pca_iris.py`

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      <div class="sphx-glr-thumbnail-title">PCA example with Iris Data-set</div>
    </div>


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    <div class="sphx-glr-thumbcontainer" tooltip="Transform a signal as a sparse combination of Ricker wavelets. This example visually compares d...">

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  .. image:: /auto_examples/decomposition/images/thumb/sphx_glr_plot_sparse_coding_thumb.png
    :alt:

  :ref:`sphx_glr_auto_examples_decomposition_plot_sparse_coding.py`

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      <div class="sphx-glr-thumbnail-title">Sparse coding with a precomputed dictionary</div>
    </div>


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    </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_sparse_coding