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 adds a bunch of new image processing routines as well as many minor usability improvements and bug fixes.
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About: Classification and Regression Training Changes:Fetched by r-cran-robot on 2018-01-01 00:00:05.042473
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About: ITE (Information Theoretical Estimators) is capable of estimating many different variants of entropy, mutual information, divergence, association measures, cross quantities and kernels on distributions. Thanks to its highly modular design, ITE supports additionally (i) the combinations of the estimation techniques, (ii) the easy construction and embedding of novel information theoretical estimators, and (iii) their immediate application in information theoretical optimization problems. Changes:
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About: Armadillo is a high quality C++ library for linear algebra & scientific computing, aiming towards a good balance between speed and ease of use. The function syntax is deliberately similar to MATLAB. Useful for algorithm development directly in C++, or quick conversion of research code into production environments (eg. software & hardware products). Changes:
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About: A fast, flexible C++ machine learning library, with bindings to other languages. Changes:Released June 8th, 2018.
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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 features the work of our 8 GSoC 2014 students [student; mentors]:
It also contains several cleanups and bugfixes: Features
Bugfixes
Cleanup and API Changes
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About: MyMediaLite is a lightweight, multi-purpose library of recommender system algorithms. Changes:Mostly bug fixes. For details see: https://github.com/zenogantner/MyMediaLite/blob/master/doc/Changes
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About: Universal Python-written numerical optimization toolbox. Problems: NLP, LP, QP, NSP, MILP, LSP, LLSP, MMP, GLP, SLE, MOP etc; general logical constraints, categorical variables, automatic differentiation, stochastic programming, interval analysis, many other goodies Changes:http://openopt.org/Changelog
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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:This release include a lot of bug fixes and improvements. Some of these are detailed at http://jira.pentaho.com/projects/DATAMINING/issues/DATAMINING-771 As usual, for a complete list of changes refer to the changelogs.
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About: Mining Association Rules and Frequent Itemsets Changes:Fetched by r-cran-robot on 2018-09-01 00:00:03.513366
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About: A thin Python wrapper that uses the javabridge Python library to communicate with a Java Virtual Machine executing Weka API calls. Changes:
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About: A platform-independent C++ framework for machine learning, graphical models, and computer vision research and development. Changes:Version 1.9:
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About: NaN-toolbox is a statistics and machine learning toolbox for handling data with and without missing values. Changes:Changes in v.3.1.2 - improve configuration and build system - support of more platforms (including Octave 4.2.0) improved Changes in v.3.0.3 - improve compatibility for Octave on Windows Changes in v.3.0.1 - fix packaging for octave Changes in v.2.8.5 - bug fix: trimmean - compiler support for gcc-5 and clang - fix typos For details see the CHANGELOG at http://pub.ist.ac.at/~schloegl/matlab/NaN/CHANGELOG
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About: mlpy is a Python module for Machine Learning built on top of NumPy/SciPy and of GSL. Changes:New features:
Fix:
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About: A Tool for Embedding Strings in Vector Spaces Changes:Support for explicit selection of granularity added. Several minor bug fixes. We have reached 1.0
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About: The scikit-learn project is a machine learning library in Python. Changes:Update for 0.18 .1
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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:2016-06-09 Version 4.7 Development and release branches available at https://github.com/gpstuff-dev/gpstuff New features
Improvements
Bugfixes
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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 non-Gaussian likelihoods (Laplace's Method, Expectation Propagation, Variational Bayes) as well for large datasets (FITC, VFE, KISS-GP). A wide range of covariance, likelihood, mean and hyperprior functions allows to create very complex GP models. Changes:Logdet-estimation functionality for grid-based approximate covariances
More generic infEP functionality
New infKL function contributed by Emtiyaz Khan and Wu Lin
Time-series covariance functions on the positive real line
New covariance functions
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About: Model-Based Boosting Changes:Fetched by r-cran-robot on 2013-04-01 00:00:06.324985
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About: A Laboratory for Recursive Partytioning Changes:Fetched by r-cran-robot on 2013-04-01 00:00:06.775432
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