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<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN"
"http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd">
<html xmlns="http://www.w3.org/1999/xhtml">
<head>
<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
<title>Homepage — Modular toolkit for Data Processing (MDP)</title>
<link rel="stylesheet" href="_static/mdp.css" type="text/css" />
<link rel="stylesheet" href="_static/pygments.css" type="text/css" />
<script type="text/javascript">
var DOCUMENTATION_OPTIONS = {
URL_ROOT: './',
VERSION: '3.6',
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<div id="header">
<table width="100%">
<tr>
<td class="td_header_left">
<a href="https://mdp-toolkit.github.io">
Modular toolkit for<br />Data Processing
</a>
</td>
<td class="td_header_right">
<a href="examples/logo/logo_animation.html">
<img src="_static/logo.png" alt="MDP logo"
title="click to see the animated logo!" class="img_header"/>
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<div class="sphinxsidebar" role="navigation" aria-label="main navigation">
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<div class="navigation_title"><a href="#">Home</a></div>
<ul>
<li class="toctree-l1"><a class="reference internal" href="install.html">Installation</a></li>
<li class="toctree-l1"><a class="reference internal" href="documentation.html">Documentation</a></li>
<li class="toctree-l1"><a class="reference internal" href="how_to_cite_mdp.html">How to cite MDP</a></li>
<li class="toctree-l1"><a class="reference internal" href="contact.html">Contact</a></li>
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<div class="admonition-news admonition">
<p class="first admonition-title">News</p>
<p>01.05.2020</p>
<blockquote class="last">
<div><p>MDP 3.6 released!
Some of the most compelling new features of MDP 3.6 are</p>
<ul class="simple">
<li>A new online mode to enable use of MDP in reinforcement learning using
OnlineNode, OnlineFlow and other new nodes.
This notably includes incremental Slow Feature Analysis in IncSFANode.</li>
<li>SFA-based supervised learning, specifically graph-based SFA nodes
GSFANode as well as iGSFANode, and hierarchical GSFA (HGSFA).</li>
<li>New solvers in SFA-node that are robust against rank deficiencies in the
covariance matrix. This cures the common issue
SymeigException (‘Covariance matrices may be singular’).</li>
<li>A new family of expansion nodes, including Legendre, Hermite and
Chebyshev polynomials allows for numerically stable data expansion
to high degrees.</li>
<li>VartimeSFANode supports SFA on data with non-constant time increments.
This node is a pilot effort to support non-constant time increments in
various mdp nodes.</li>
</ul>
<p>MDP 3.6 supports the newest versions of Python, NumPy, SciPy and
scikit-learn. More specifically, it supports Python 3.5-3.8 and 2.7. It is
the last release that officially supports Python 2.7.</p>
</div></blockquote>
</div>
<p><strong>Modular toolkit for Data Processing (MDP)</strong> is a Python data processing framework.</p>
<p>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.</p>
<p>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.</p>
<p>The base of available algorithms is steadily increasing and includes
signal processing methods (Principal Component Analysis,
Independent Component Analysis, Slow Feature Analysis),
manifold learning methods ([Hessian] Locally Linear Embedding),
several classifiers, probabilistic methods (Factor Analysis, RBM),
data pre-processing methods, and many others.</p>
<p id="using-mdp-is-as-easy">Using MDP is as easy as:</p>
<div class="highlight-default"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="kn">import</span> <span class="nn">mdp</span>
<span class="gp">>>> </span><span class="c1"># perform PCA on some data x</span>
<span class="gp">>>> </span><span class="n">y</span> <span class="o">=</span> <span class="n">mdp</span><span class="o">.</span><span class="n">pca</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>
<span class="gp">>>> </span><span class="c1"># perform ICA on some data x using single precision</span>
<span class="gp">>>> </span><span class="n">y</span> <span class="o">=</span> <span class="n">mdp</span><span class="o">.</span><span class="n">fastica</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="s1">'float32'</span><span class="p">)</span>
</pre></div>
</div>
<p>To learn more about MDP, read through the <a class="reference internal" href="documentation.html#documentation"><span class="std std-ref">Documentation</span></a>.</p>
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Last updated on
2020-12-16 6:49:02 PM Coordinated Universal Time
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