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About: A C++ toolkit containing machine learning algorithms and tools that facilitate creating complex software in C++ to solve real world problems. Changes:This release adds a general purpose implementation of the OCA optimizer, OCAS SVM trainer, and support for loading and saving LIBSVM formatted data files.
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About: The CTBN-RLE is a C++ package of executables and libraries for inference and learning algorithms for continuous time Bayesian networks (CTBNs). Changes:Minor code changes (a few compilation issues, #define .h guard name changes).
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About: A Java framework for statistical analysis and classification of biological sequences Changes:March 2, 2010: Jstacs 1.3.1 released
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About: libDAI provides FOSS implementations of various (approximate) inference methods for graphical models with discrete variables, including Bayesian networks and Markov Random Fields. Changes:New features include: Apart from that, this release various code cleanups, bug fixes, added examples, and documentation improvements.
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About: Armadillo is a template C++ linear algebra library aiming towards a good balance between speed and ease of use. Matrix decompositions are provided through optional integration with LAPACK and ATLAS. Changes:
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About: The Weka workbench contains a collection of visualization tools and algorithms for data analysis and predictive modelling, together with graphical user interfaces for easy access to this [...] Changes:Initial Announcement on mloss.org.
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About: Universal Python-written numerical optimization toolbox. Problems: NLP, LP, QP, NSP, MILP, LSP, LLSP, MMP, GLP, SLE etc; automatic differentiation is available Changes:http://openopt.org/Changelog
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About: A Java library to create, process and manage mixtures of exponential families. Changes:Initial Announcement on mloss.org.
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About: Machine Learning PYthon (mlpy) is a high-performance Python package for predictive modeling. Changes:New features:
Bug fixes:
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About: MLPACK is the first comprehensive scalable machine learning library. Changes:Initial Announcement on mloss.org.
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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 release contains several enhancements, cleanups and bugfixes: Features
Bugfixes
Cleanup and API Changes
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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 1.2.3
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About: SHARK is a modular C++ library for the design and optimization of adaptive systems. It provides various machine learning and computational intelligence techniques. Changes:
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About: Elefant is an open source software platform for the Machine Learning community licensed under the Mozilla Public License (MPL) and developed using Python, C, and C++. We aim to make it the platform [...] Changes:This release contains the Stream module as a first step in the direction of providing C++ library support. Stream aims to be a software framework for the implementation of large scale online learning algorithms. Large scale, in this context, should be understood as something that does not fit in the memory of a standard desktop computer. Added Bundle Methods for Regularized Risk Minimization (BMRM) allowing to choose from a list of loss functions and solvers (linear and quadratic). Added the following loss classes: BinaryClassificationLoss, HingeLoss, SquaredHingeLoss, ExponentialLoss, LogisticLoss, NoveltyLoss, LeastMeanSquareLoss, LeastAbsoluteDeviationLoss, QuantileRegressionLoss, EpsilonInsensitiveLoss, HuberRobustLoss, PoissonRegressionLoss, MultiClassLoss, WinnerTakesAllMultiClassLoss, ScaledSoftMarginMultiClassLoss, SoftmaxMultiClassLoss, MultivariateRegressionLoss Graphical User Interface provides now extensive documentation for each component explaining state variables and port descriptions. Changed saving and loading of experiments to XML (thereby avoiding storage of large input data structures). Unified automatic input checking via new static typing extending Python properties. Full support for recursive composition of larger components containing arbitrary statically typed state variables.
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About: RL-Glue allows agents, environments, and experiments written in Java, C/C++, Matlab, Python, and Lisp to inter operate, accelerating research by promoting software re-use in the community. Changes:RL-Glue paper has been published in JMLR.
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About: BioSig is a software library for biomedical signal processings. Besides several other modules, one modul (t400) provides a common interface (train_sc.m and test_sc.m) to various classification [...] Changes:Update of project information: machine learning and classification tools are moved to the NaN-toolbox.
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About: The Computational Infrastructure for Operations Research (COIN-OR) project is an initiative to spur the development of open-source software for the operations research community. Changes:Initial Announcement on mloss.org.
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About: SeDuMi is a software package to solve optimization problems over symmetric cones. This includes linear, quadratic, second order conic and semidefinite optimization, and any combination of these. Changes:Initial Announcement on mloss.org.
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About: This toolbox provides functions for maximizing and minimizing submodular set functions, with applications to Bayesian experimental design, inference in Markov Random Fields, clustering and others. Changes:Initial Announcement on mloss.org.
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About: LibSGDQN proposes an implementation of SGD-QN, a carefully designed quasi-Newton stochastic gradient descent solver for linear SVMs. Changes:small bug fix (thx nicolas ;)
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