About: C++ software for statistical classification, probability estimation and interpolation/nonlinear regression using variable bandwidth kernel estimation. Changes:New in Version 0.9.7:

About: This project is a C++ toolkit containing machine learning algorithms and tools that facilitate creating complex software in C++ to solve real world problems. Changes:The major new feature in this release is a Python API for training histogramoforientedgradient based object detectors and examples showing how to use this type of detector to perform realtime face detection. Additionally, this release also adds simpler interfaces for learning to solve assignment and multitarget tracking problems.

About: MOSIS is a modularized framework for signal processing, stream analysis, machine learning and stream mining applications. 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: The SHOGUN machine learning toolbox's focus is on large scale learning methods with focus on Support Vector Machines (SVM), providing interfaces to python, octave, matlab, r and the command line. Changes:This is mostly a bugfix release: Features
Bugfixes

About: DRVQ is a C++ library implementation of dimensionalityrecursive vector quantization, a fast vector quantization method in highdimensional Euclidean spaces under arbitrary data distributions. It is an approximation of kmeans that is practically constant in data size and applies to arbitrarily high dimensions but can only scale to a few thousands of centroids. As a byproduct of training, a tree structure performs either exact or approximate quantization on trained centroids, the latter being not very precise but extremely fast. Changes:Initial Announcement on mloss.org.

About: AprilANN toolkit (A Pattern Recognizer In Lua with Artificial Neural Networks). This toolkit incorporates ANN algorithms (as dropout, stacked denoising autoencoders, convolutional neural networks), with other pattern recognition methods as hiddem makov models (HMMs) among others. Changes:Added automatic differentiation package. Removed some bugs and memory leaks. Better decouplong between ANN modules, optimizer objects and loss functions. Addition of Conjugate Gradient, Rprop and Quickprop algorithms.

About: A Tool for Measuring String Similarity Changes:Initial Announcement on mloss.org.

About: A Tool for Embedding Strings in Vector Spaces Changes:Support for new version of libarchive. Several major and minor bug fixes.

About: A Content Anomaly Detector based on nGrams Changes:Fixes a bug in the unit testing framework on Windows

About: a dbms for resonating neural networks. Create and use different types of machine learning algorithms. Changes:AIML compatible (AIML files can be imported); new 'Grid channel' for developing board games; improved topics editor; new demo project: ALice (from AIML); lots of bugfixes and speed improvements

About: Software to perform isoline retrieval, retrieve isolines of an atmospheric parameter from a nadirlooking satellite. Changes:Added screenshot, keywords

About: A work in progress Changes:Initial Announcement on mloss.org.

About: OpenViBE is an opensource platform that enables to design, test and use BrainComputer Interfaces (BCI). Broadly speaking, OpenViBE can be used in many realtime Neuroscience applications [...] Changes:New release 0.8.0.

About: The SUMO Toolbox is a Matlab toolbox that automatically builds accurate surrogate models (also known as metamodels or response surface models) of a given data source (e.g., simulation code, data set, script, ...) within the accuracy and time constraints set by the user. The toolbox minimizes the number of data points (which it selects automatically) since they are usually expensive. Changes:Incremental update, fixing some cosmetic issues, coincides with JMLR publication.

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: The Universal Java Matrix Package (UJMP) is a data processing tool for Java. Unlike JAMA and Colt, it supports multithreading and is therefore much faster on current hardware. It does not only support matrices with double values, but instead handles every type of data as a matrix through a common interface, e.g. CSV files, Excel files, images, WAVE audio files, tables in SQL data bases, and much more. Changes:Meta data updated.
