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

About: MOSIS is a modularized framework for signal processing, stream analysis, machine learning and stream mining applications. Changes:

About: The Rchemcpp package implements the marginalized graph kernel and extensions, Tanimoto kernels, graph kernels, pharmacophore and 3D kernels suggested for measuring the similarity of molecules. Changes:Moved from CRAN to Bioconductor. Improved handling of molecules, visualization and examples.

About: Python Framework for Vector Space Modelling that can handle unlimited datasets (streamed input, online algorithms work incrementally in constant memory). Changes:

About: The OrGanic Environment for Reservoir computing (Oger) toolbox is a Python toolbox for rapidly building, training and evaluating modular learning architectures on large datasets. Changes:Initial Announcement on mloss.org.

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: The KernelMachine Library is a free (released under the LGPL) C++ library to promote the use of and progress of kernel machines. Changes:Updated mloss entry (minor fixes).

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

About: LDPar is an efficient datadriven dependency parser. You can train your own parsing model on treebank data and parse new data using the induced model. Changes:Initial Announcement on mloss.org.

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 Ktree is a scalable approach to clustering inspired by the B+tree and kmeans algorithms. Changes:Release of Ktree implementation in Python. This is targeted at a research and rapid prototyping audience.

About: Moses is a statistical machine translation system that allows you to automatically train translation models for any language pair. All you need is a collection of translated texts (parallel corpus). An efficient search algorithm finds quickly the highest probability translation among the exponential number of choices. Changes:Initial Announcement on mloss.org.

About: GPUML is a library that provides a C/C++ and MATLAB interface for speeding up the computation of the weighted kernel summation and kernel matrix construction on GPU. These computations occur commonly in several machine learning algorithms like kernel density estimation, kernel regression, kernel PCA, etc. Changes:Initial Announcement on mloss.org.

About: The JINSECT toolkit is a Javabased toolkit and library that supports and demonstrates the use of ngram graphs within Natural Language Processing applications, ranging from summarization and summary evaluation to text classi?cation and indexing. Changes:

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.

About: CRF++ is a simple, customizable, and open source implementation of Conditional Random Fields (CRFs) for segmenting/labeling sequential data. Changes:Initial Announcement on mloss.org.

About: This software is aimed at performing supervised/unsupervised learning on graph data, where each graph is represented as binary indicators of subgraph features. Changes:Initial Announcement on mloss.org.

About: A library for fast computation of Gauss transforms in multiple dimensions, using the Improved Fast Gauss Transform and a tree data structure. This library is useful for efficient Kernel Density [...] Changes:Initial Announcement on mloss.org.

About: Aleph is both a multiplatform machine learning framework aimed at simplicity and performance, and a library of selected stateoftheart algorithms. Changes:Initial Announcement on mloss.org.

About: This software package includes the ART algorithms for unsupervised learning only. It is a family of four programs based on different ART algorithms (ART 1, ART 2A, ART 2AC and ART Distance). All of [...] Changes:Initial Announcement on mloss.org.
