We are glad to announce release 3.3 of the Modular toolkit for Data
Processing (MDP). This a bug-fix release, all current users are
invited to upgrade.
MDP is a Python library of widely used data processing algorithms
that can be combined according to a pipeline analogy to build more
complex data processing software. The base of available algorithms
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.
What's new in version 3.3?
- support sklearn versions up to 0.12
- cleanly support reload
- fail gracefully if pp server does not start
- several bug-fixes and improvements
Mailing list: http://lists.sourceforge.net/mailman/listinfo/mdp-toolkit-users
We thank the contributors to this release: Philip DeBoer, Yaroslav Halchenko.
The MDP developers,
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