About: A Kmeans clustering implementation for commandline, Python, Matlab and C. This algorithm yields the very same solution as standard Kmeans, even after each iteration. However it uses some triangle [...] Changes:Initial Announcement on mloss.org.

About: The GPML toolbox is a flexible and generic Octave/Matlab implementation of inference and prediction with Gaussian process models. The toolbox offers exact inference, approximate inference for nonGaussian likelihoods (Laplace's Method, Expectation Propagation, Variational Bayes) as well for large datasets (FITC, VFE, KISSGP). A wide range of covariance, likelihood, mean and hyperprior functions allows to create very complex GP models. Changes:A major code restructuring effort did take place in the current release unifying certain inference functions and allowing more flexibility in covariance function composition. We also redesigned the whole derivative computation pipeline to strongly improve the overall runtime. We finally include gridbased covariance approximations natively. More generic sparse approximation using Power EP
Approximate covariance object unifying sparse approximations, gridbased approximations and exact covariance computations
Hiearchical structure of covariance functions
Faster derivative computations for mean and cov functions
New mean functions
New optimizer
New GLM link function
Smaller fixes

About: Python module to ease pattern classification analyses of large datasets. It provides highlevel abstraction of typical processing steps (e.g. data preparation, classification, feature selection, [...] Changes:
This release aggregates all the changes occurred between official
releases in 0.4 series and various snapshot releases (in 0.5 and 0.6
series). To get better overview of high level changes see
:ref:
Also adapts changes from 0.4.6 and 0.4.7 (see corresponding changelogs).
This is a special release, because it has never seen the general public.
A summary of fundamental changes introduced in this development version
can be seen in the :ref: Most notably, this version was to first to come with a comprehensive twoday workshop/tutorial.
A bugfix release
A bugfix release

About: The GPstuff toolbox is a versatile collection of Gaussian process models and computational tools required for inference. The tools include, among others, various inference methods, sparse approximations and model assessment methods. Changes:20160609 Version 4.7 Development and release branches available at https://github.com/gpstuffdev/gpstuff New features
Improvements
Bugfixes

About: FLANN is a library for performing fast approximate nearest neighbor searches in high dimensional spaces. It contains a collection of algorithms we found to work best for nearest neighbor search. Changes:See project page for changes.

About: The apcluster package implements Frey's and Dueck's Affinity Propagation clustering in R. The package further provides leveraged affinity propagation, exemplarbased agglomerative clustering, and various tools for visual analysis of clustering results. Changes:

About: A thin Python wrapper that uses the javabridge Python library to communicate with a Java Virtual Machine executing Weka API calls. Changes:

About: Locally Weighted Projection Regression (LWPR) is a recent algorithm that achieves nonlinear function approximation in high dimensional spaces with redundant and irrelevant input dimensions. At its [...] Changes:Version 1.2.4

About: Mining Association Rules and Frequent Itemsets Changes:Fetched by rcranrobot on 20161201 00:00:03.836252

About: The Accord.NET Framework is a .NET machine learning framework combined with audio and image processing libraries completely written in C#. It is a complete framework for building productiongrade computer vision, computer audition, signal processing and statistics applications even for commercial use. A comprehensive set of sample applications provide a fast start to get up and running quickly, and an extensive online documentation helps fill in the details. Changes:Adding a large number of new distributions, such as AndersonDaring, ShapiroWilk, Inverse ChiSquare, Lévy, Folded Normal, Shifted LogLogistic, Kumaraswamy, Trapezoidal, Uquadratic and BetaPrime distributions, BirnbaumSaunders, Generalized Normal, Gumbel, Power Lognormal, Power Normal, Triangular, Tukey Lambda, Logistic, Hyperbolic Secant, Degenerate and General Continuous distributions. Other additions include new statistical hypothesis tests such as AndersonDaring and ShapiroWilk; as well as support for all of LIBLINEAR's support vector machine algorithms; and format reading support for MATLAB/Octave matrices, LibSVM models, sparse LibSVM data files, and many others. For a complete list of changes, please see the full release notes at the release details page at: https://github.com/accordnet/framework/releases
