About: A MATLAB spectral clustering package to deal with large data sets. Our tool can handle large data sets (200,000 RCV1 data) on a 4GB memory general machine. Spectral clustering algorithm has been [...] Changes:

About: Automatic Analysis of Malware Behavior using Machine Learning Changes:Support for new version of libarchive. Minor bug fixes.

About: The library is focused on implementation of propagation based approximate inference methods. Also implemented are a clique tree based exact inference, Gibbs sampling, and the mean field algorithm. Changes:Initial Announcement on mloss.org.

About: Tapkee is an efficient and flexible C++ template library for dimensionality reduction. Changes:Initial Announcement on mloss.org.

About: Generalized linear and additive models by likelihood based boosting Changes:Fetched by rcranrobot on 20130401 00:00:04.893311

About: An implementation of the infinite hidden Markov model. Changes:Since 0.4: Removed dependency from lightspeed (now using statistics toolbox). Updated to newer matlab versions.

About: Variational Bayesian inference tools for Python Changes:

About: BCPy2000 provides a platform for rapid, flexible development of experimental BrainComputer Interface systems based on the BCI2000.org project. From the developer's point of view, the implementation [...] Changes:Bugfixes and tuneups, and an expanded set of (some more, some lessdocumented, optional tools)

About: Somoclu is a massively parallel implementation of selforganizing maps. It relies on OpenMP for multicore execution, MPI for distributing the workload, and it can be accelerated by CUDA on a GPU cluster. A sparse kernel is also included, which is useful for training maps on vector spaces generated in text mining processes. Apart from a command line interface, Python, Julia, R, and MATLAB are supported. Changes:

About: The Maja Machine Learning Framework (MMLF) is a general framework for problems in the domain of Reinforcement Learning (RL) written in python. It provides a set of RL related algorithms and a set of benchmark domains. Furthermore it is easily extensible and allows to automate benchmarking of different agents. Changes:
