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

About: Armadillo is a template C++ linear algebra library aiming towards a good balance between speed and ease of use, with a function syntax similar to MATLAB. Matrix decompositions are provided through optional integration with LAPACK, or one of its high performance dropin replacements (eg. Intel MKL, OpenBLAS). Changes:

About: Kernelbased Learning Platform (KeLP) is Java framework that supports the implementation of kernelbased learning algorithms, as well as an agile definition of kernel functions over generic data representation, e.g. vectorial data or discrete structures. The framework has been designed to decouple kernel functions and learning algorithms, through the definition of specific interfaces. Once a new kernel function has been implemented, it can be automatically adopted in all the available kernelmachine algorithms. KeLP includes different Online and Batch Learning algorithms for Classification, Regression and Clustering, as well as several Kernel functions, ranging from vectorbased to structural kernels. It allows to build complex kernel machine based systems, leveraging on JSON/XML interfaces to instantiate prediction models without writing a single line of code. Changes:In addition to minor bug fixes, this release includes:
Check out this new version from our repositories. API Javadoc is already available. Your suggestions will be very precious for us, so download and try KeLP 2.0.1!

About: A scalable, fast C++ machine learning library, with emphasis on usability. Changes:
See also https://mailman.cc.gatech.edu/pipermail/mlpack/2015December/000706.html for more information.

About: NaNtoolbox is a statistics and machine learning toolbox for handling data with and without missing values. Changes:Changes in v.2.8.5  bug fix: trimmean  compiler support for gcc5 and clang  fix typos For details see the CHANGELOG at http://pub.ist.ac.at/~schloegl/matlab/NaN/CHANGELOG

About: The Advanced Data mining And Machine learning System (ADAMS) is a novel, flexible workflow engine aimed at quickly building and maintaining realworld, complex knowledge workflows. Changes:Some highlights of this release:

About: MLweb is an open source project that aims at bringing machine learning capabilities into web pages and web applications, while maintaining all computations on the client side. It includes (i) a javascript library to enable scientific computing within web pages, (ii) a javascript library implementing machine learning algorithms for classification, regression, clustering and dimensionality reduction, (iii) a web application providing a matlablike development environment. Changes:

About: ELKI is a framework for implementing datamining algorithms with support for index structures, that includes a wide variety of clustering and outlier detection methods. Changes:Additions and Improvements from ELKI 0.6.0: ELKI is now available on Maven: https://search.maven.org/#artifactdetailsde.lmu.ifi.dbs.elkielki0.7.0jar Please clone https://github.com/elkiproject/exampleelkiproject for a minimal project example. Uncertain data types, and clustering algorithms for uncertain data. Major refactoring of distances  removal of Distance values and removed support for nondoublevalued distance functions (in particular DoubleDistance was removed). While this reduces the generality of ELKI, we could remove about 2.5% of the codebase by not having to have optimized codepaths for doubledistance anymore. Generics for distances were present in almost any distancebased algorithm, and we were also happy to reduce the use of generics this way. Support for nondoublevalued distances can trivially be added again, e.g. by adding the specialization one level higher: at the query instead of the distance level, for example. In this process, we also removed the Generics from NumberVector. The objectbased get was deprecated for a good reason long ago, and e.g. doubleValue are more efficient (even for nonDoubleVectors). Dropped some longdeprecated classes. Kmeans:
CLARA clustering. Xmeans. Hierarchical clustering:
LSDBC clustering. EM clustering was refactored and moved into its own package. The new version is much more extensible. OPTICS clustering:
Outlier detection:
Parallel computation framework, and some parallelized algorithms
LibSVM format parser. kNN classification (with index acceleration). Internal cluster evaluation:
Statistical dependence measures:
Distance functions:
Preprocessing:
Indexing improvements:
Frequent Itemset Mining:
Uncertain clustering:
Mathematics:
MiniGUI has two "secret" new options: minigui.last minigui.autorun to load the last saved configuration and run it, for convenience. Logging API has been extended, to make logging more convenient in a number of places (saving some lines for progress logging and timing).

About: Software for Automatic Construction and Inference of DBNs Based on Mathematical Models Changes:Initial Announcement on mloss.org.

About: An opensource Python toolbox to analyze mobile phone metadata. Changes:Initial Announcement on mloss.org.

About: PCVM library a c++/armadillo implementation of the Probabilistic Classification Vector Machine. Changes:30.10.2015 * code has been revised in some places fixing also some errors different multiclass schemes and hdf5 file support added. Some speed ups and memory savings by better handling of intermediate objects. 27.05.2015:  Matlab binding under Windows available. Added a solution file for VS'2013 express to compile a matlab mex binding. Can not yet confirm that under windows the code is really using multiple cores (under linux it does) 29.04.2015 * added an implementation of the Nystroem based PCVM includes: Nystroem based singular value decomposition (SVD), eigenvalue decomposition (EVD) and pseudoinverse calculation (PINV) 22.04.2015 * implementation of the PCVM released

About: Variational Bayesian inference tools for Python Changes:

About: The Cognitive Foundry is a modular Java software library of machine learning components and algorithms designed for research and applications. Changes:

About: This project is a C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real world problems. Changes:This release has focused on build system improvements, both for the Python API and C++ builds using CMake. This includes adding a setup.py script for installing the dlib Python API as well as a make install target for installing a C++ shared library for nonPython use.

About: A Machine Learning framework for ObjectiveC and Swift (OS X / iOS) Changes:Initial Announcement on mloss.org.

About: Rival is an open source Java toolkit for recommender system evaluation. It provides a simple way to create evaluation results comparable across different recommendation frameworks. Changes:Initial Announcement on mloss.org.

About: R package implementing statistical test and post hoc tests to compare multiple algorithms in multiple problems. Changes:Initial Announcement on mloss.org.

About: A Deep Learning API and server Changes:Initial Announcement on mloss.org.

About: streamDM is a new open source data mining and machine learning library, designed on top of Spark Streaming, an extension of the core Spark API that enables scalable, highthroughput, faulttolerant stream processing of data streams. Changes:Initial Announcement on mloss.org.
