About: HierLearning is a C++11 implementation of a general-purpose, multi-agent, hierarchical reinforcement learning system for sequential decision problems.

Initial Announcement on mloss.org.

About: Jubatus is a general framework library for online and distributed machine learning. It currently supports classification, regression, clustering, recommendation, nearest neighbors, anomaly detection, and graph analysis. Loose model sharing provides higher scalability, better performance, and real-time capabilities, by combining online learning with distributed computations.

0.5.0 add new supports for clustering and nearest neighbors. For more detail, see http://t.co/flMcTcYZVs

About: Bayesian Model Averaging for linear models with a wide choice of (customizable) priors. Built-in priorss include coefficient priors (fixed, flexible and hyper-g priors), 5 kinds of model priors, moreover model sampling by enumeration or various MCMC approaches.

Initial Announcement on mloss.org.

About: HLearn makes simple machine learning routines available in Haskell by expressing them according to their algebraic structure

Updated to version 1.0

About: A comprehensive data mining environment, with a variety of machine learning components.

Modifications following feedback from Knime main Author.

About: This toolbox implements models for Bayesian mixed-effects inference on classification performance in hierarchical classification analyses.

In addition to the existing MATLAB implementation, the toolbox now also contains an R package of the variational Bayesian algorithm for mixed-effects inference.

About: This package contains a python and a matlab implementation of the most widely used algorithms for multi-armed bandit problems. The purpose of this package is to provide simple environments for comparison and numerical evaluation of policies.

Initial Announcement on mloss.org.