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:

About: GibbsLDA++: A C/C++ Implementation of Latent Dirichlet Allocation (LDA) using Gibbs Sampling for parameter estimation and inference. GibbsLDA++ is fast and is designed to analyze hidden/latent topic [...] Changes:Initial Announcement on mloss.org.

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

About: Improved Predictors Changes:Fetched by rcranrobot on 20130401 00:00:05.613011

About: Pyriel is a Python system for learning classification rules from data. Unlike other rule learning systems, it is designed to learn rule lists that maximize the area under the ROC curve (AUC) instead of accuracy. Pyriel is mostly an experimental research tool, but it's robust and fast enough to be used for lightweight industrial data mining. Changes:1.5 Changed CF (confidence factor) to do LaPlace smoothing of estimates. New flag "scoreforclass C" causes scores to be computed relative to a given (positive) class. For twoclass problems. Fixed bug in example sampling code (sample n) Fixed bug keeping oldstyle example formats (terminated by dot) from working. More code restructuring.

About: Bayesian treed Gaussian process models Changes:Fetched by rcranrobot on 20120201 00:00:11.834310

About: VR Changes:Fetched by rcranrobot on 20091003 07:16:05.643423

About: JProGraM (PRObabilistic GRAphical Models in Java) is a statistical machine learning library. It supports statistical modeling and data analysis along three main directions: (1) probabilistic graphical models (Bayesian networks, Markov random fields, dependency networks, hybrid random fields); (2) parametric, semiparametric, and nonparametric density estimation (Gaussian models, nonparanormal estimators, Parzen windows, NadarayaWatson estimator); (3) generative models for random networks (smallworld, scalefree, exponential random graphs, Fiedler random graphs/fields), subgraph sampling algorithms (random walk, snowball, etc.), and spectral decomposition. Changes:JProGraM 13.2  CHANGE LOG Release date: February 13, 2012 New features:  Support for Fiedler random graphs/random field models for largescale networks (ninofreno.graph.fiedler package);  Various bugfixes and enhancements (especially in the ninofreno.graph and ninofreno.math package).

About: Matlab Multiple Kernel Learning toolbox. Features : MKL for SVM Classification, Regression and MultiClass. It needs SVMKM Toolbox Changes:Initial Announcement on mloss.org.

About: Nieme is a C++ machine learning library for largescale classification, regression and ranking. It provides a simple interface available in C++, Python and Java and a user interface for visualization. Changes:Released Nieme 1.0
