Dear NumPy and SciPy users,
we are proud to announce release 2.3 of the Modular toolkit for Data Processing
(MDP): a Python data processing framework. The base of readily available
algorithms includes Principal Component Analysis (PCA and NIPALS), four flavors
of Independent Component Analysis (CuBICA, FastICA, TDSEP, and JADE), Slow
Feature Analysis, Independent Slow Feature Analysis, Gaussian Classifiers,
Growing Neural Gas, Fisher Discriminant Analysis, Factor Analysis, Restricted
Boltzmann Machine, and many more.
What's new in version 2.3?
- Enhanced PCA nodes (with SVD, automatic dimensionality reduction, and
- A complete implementation of the FastICA algorithm.
- JADE and TDSEP nodes for more fun with ICA.
- Restricted Boltzmann Machine nodes.
- The new subpackage "hinet" allows combining nodes in arbitrary feed-forward
network architectures with a HTML visualization tool.
- The tutorial has been updated with a section on hierarchical networks.
- MDP integrated into the official Debian repository as "python-mdp".
- A bunch of bug-fixes.