.. automodule:: skmatter .. raw:: html
.. only:: html :ref:`getting_started-selection` .. image:: /examples/selection/images/thumb/sphx_glr_FeatureSelection-WHODataset_thumb.png :alt: .. raw:: html

Supervised and unsupervised selection methods based on CUR matrix decomposition and Farthest Point Sampling.

.. only:: html :ref:`getting_started-pcovr` .. image:: /examples/pcovr/images/thumb/sphx_glr_PCovR_thumb.png :alt: .. raw:: html

Utilises a combination between a PCA-like and a LR-like loss to determine the decomposition matrix to project feature into latent space

.. only:: html :ref:`getting_started-reconstruction` .. image:: /examples/reconstruction/images/thumb/sphx_glr_PlotLFRE_thumb.png :alt: .. raw:: html

Error measures for quantifying the linear decodable information capacity between features


.. include:: ../../README.rst :start-after: marker-issues :end-before: marker-contributing .. toctree:: :hidden: getting-started installation references/index tutorials contributing changelog bibliography If you would like to contribute to scikit-matter, check out our :ref:`contributing` page!