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           Modular toolkit for Data Processing (MDP)
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        Authors: Pietro Berkes, Niko Wilbert, and Tiziano Zito
        Email:   berkes@brandeis.edu, mail@nikowilbert.de,
                 tiziano.zito@bccn-berlin.de
        Homepage: http://mdp-toolkit.sourceforge.net
        Download: http://sourceforge.net/projects/mdp-toolkit
        Current release: 2.4
        License: LGPL v3 (see COPYING and COPYING.LESSER file)
        Date: Sat Oct 18 2008

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Semi-automatically generated by links from
  http://mdp-toolkit.sourceforge.net/index.html .


   News

               MDP 2.4 released (changes since last release):
               - new parallel package
   17.10.2008: - new nodes for Locally Linear Embedding dimensionality
               reduction
               - started code migration towards Python 3.0
   15.05.2008: MDP 2.3 released.

   Modular toolkit  for Data  Processing (MDP)  is a  Python data  processing
   framework.

   From the  user's  perspective,  MDP  is a  collection  of  supervised  and
   unsupervised learning algorithms and other data processing units that  can
   be combined into data processing  sequences and more complex  feed-forward
   network architectures.

   From the scientific developer's perspective,  MDP is a modular  framework,
   which can easily be expanded. The implementation of new algorithms is easy
   and intuitive. The new implemented units are then automatically integrated
   with the rest of the library.

   The base of available algorithms  is steadily increasing and includes,  to
   name but the most common,  Principal Component Analysis (PCA and  NIPALS),
   several Independent Component Analysis algorithms (CuBICA, FastICA, TDSEP,
   and  JADE),  Slow  Feature  Analysis,  Gaussian  Classifiers,   Restricted
   Boltzmann Machine, and Locally Linear Embedding.

   To learn more about MDP:

     * Introduction
     * Full list of implemented algorithms
     * Tutorial (pdf 830 KB)
     * API

   Using MDP is as easy as:

 >>> import mdp
 >>> # perform pca on some data x
 ...
 >>> y = mdp.pca(x)
 >>> # perform ica on some data x using single precision
 ...
 >>> y = mdp.fastica(x, dtype='float32')

   --------------------------------------------------------------------------

Installation

   Requirements:
   Python >= 2.4, and NumPy >= 1.1  or Scipy >= 0.5.2. The symeig package  is
   automatically used if installed.

   Download:
   You can download the last MDP release here.
   If you  want  to  live  on  the bleeding  edge,  check  out  the  MDP  svn
   repository: you can  browse the  repository or  just check  out the  trunk
   with:

 svn co https://mdp-toolkit.svn.sourceforge.net/svnroot/mdp-toolkit/mdp/trunk/mdp mdp

   Thanks to  Yaroslav Halchenko,  Debian users  can install  the  python-mdp
   package.

   Installation:
   Unpack the archive file, enter the project directory and type:

 python setup.py install

   If you want to use MDP without installing it on the system Python path:

 python setup.py install --prefix=/some_dir_in_PYTHONPATH/

   On Debian you can just type:

 aptitude update
 aptitude install python-mdp

   On Windows, the  installation of  the binary  distribution is  as easy  as
   executing the installer and following the instructions.

   Testing:
   If you have successfully installed MDP, you can test your installation  in
   a Python shell as follows:

 >>> import mdp
 >>> mdp.test()

   Demos:
   All the  code examples  shown in  the MDP  tutorial can  be found  in  the
   package installation path in the subdirectory demo.

   --------------------------------------------------------------------------

Maintainers

   MDP has been originally written by  Pietro Berkes and Tiziano Zito at  the
   Institute for Theoretical  Biology of the  Humboldt University, Berlin  in
   2003.

   Current maintainers are:

     * Pietro Berkes
     * Niko Wilbert
     * Tiziano Zito

   Yaroslav Halchenko maintains the python-mdp Debian package.

   For comments, patches, feature requests, support requests, and bug reports
   (if any) you can use the users mailing list.

   If you want  to contribute some  code or  a new algorithm,  please do  not
   hesitate to submit it!

   --------------------------------------------------------------------------

How to cite MDP

   If you use MDP for scientific purposes,  you may want to cite it. This  is
   the official way to do it:

   Berkes, P., Wilbert, N., and Zito, T. (2008)
   Modular Toolkit for Data Processing (version 2.4)
   http://mdp-toolkit.sourceforge.net

   If your paper gets published, plase send  us a reference (and even a  copy
   if you don't mind).

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References

   Visible links
   . click to see the animated logo!
	http://mdp-toolkit.sourceforge.net/logo_animation.html
   . http://mdp-toolkit.sourceforge.net/index.html
   . http://mdp-toolkit.sourceforge.net/tutorial.html
   . http://mdp-toolkit.sourceforge.net/index.html#DOWINS
   . http://mdp-toolkit.sourceforge.net/tutorial.html#node-list
   . http://mdp-toolkit.sourceforge.net/docs/api/index.html
   . http://sourceforge.net/mail/?group_id=116959
   . http://mdp-toolkit.sourceforge.net/symeig.html
   . http://mdp-toolkit.sourceforge.net/CHANGES
   . http://mdp-toolkit.sourceforge.net/tutorial.html#introduction
   . http://mdp-toolkit.sourceforge.net/tutorial.html#node-list
   . http://mdp-toolkit.sourceforge.net/tutorial.html
   . http://prdownloads.sourceforge.net/mdp-toolkit/MDP2_4_tutorial.pdf?download
   . http://mdp-toolkit.sourceforge.net/docs/api/index.html
   . http://www.python.org/
   . http://numpy.scipy.org/
   . http://www.scipy.org/
   . http://mdp-toolkit.sourceforge.net/symeig.html
   . http://sourceforge.net/project/showfiles.php?group_id=116959
   . http://sourceforge.net/svn/?group_id=116959
   . http://mdp-toolkit.svn.sourceforge.net/
   . http://mdp-toolkit.sourceforge.net/tutorial.html
   . http://people.brandeis.edu/~berkes
   . http://itb.biologie.hu-berlin.de/~zito
   . http://itb.biologie.hu-berlin.de/
   . http://www.hu-berlin.de/
   . http://people.brandeis.edu/~berkes
   . http://itb.biologie.hu-berlin.de/~wilbert
   . http://itb.biologie.hu-berlin.de/~zito
   . http://www.onerussian.com/
   . http://packages.debian.org/python-mdp
   . http://sourceforge.net/mail/?group_id=116959
   . http://mdp-toolkit.sourceforge.net/
   . http://sourceforge.net/
   . http://validator.w3.org/check?uri=referer;verbose=1
