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About: CARP: The Clustering Algorithms’ Referee Package Changes:Options to add noise, outliers, inverse Box-Cox transformation.
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About: Orange is a component-based machine learning and data mining software. It includes a friendly yet powerful and flexible graphical user interface for visual programming. For more advanced use(r)s, [...] Changes:Update for v2.0
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About: libDAI provides free & open source implementations of various (approximate) inference methods for graphical models with discrete variables, including Bayesian networks and Markov Random Fields. Changes:libDAI release 0.2.7 is a bug-fix release which fixes a bug in the junction-tree MAP inference which could yield incorrect results in some cases. This release will accompany a forthcoming JMLR publication about libDAI.
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About: Machine Learning PYthon (mlpy) is a high-performance Python package for predictive modeling. Changes:New features:
Several bugs fixed
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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: A C++ toolkit containing machine learning algorithms and tools that facilitate creating complex software in C++ to solve real world problems. Changes:Minor bug fixes
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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: 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 C++ library of machine learning algorithms and tools. Several demos are included that show how to use the library. Also, there is a script-friendly command-line interface that makes the algorithms [...] Changes:See the change log at http://waffles.sourceforge.net/changelog.html
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About: Massive Online Analysis (MOA) is a real time analytic tool for data streams. It is a software environment for implementing algorithms and running experiments for online learning from evolving data streams. MOA includes a collection of offline and online methods as well as tools for evaluation. In particular, it implements boosting, bagging, and Hoeffding Trees, all with and without Naive Bayes classifiers at the leaves. MOA supports bi-directional interaction with WEKA, the Waikato Environment for Knowledge Analysis, and it is released under the GNU GPL license. Changes:Initial Announcement on mloss.org.
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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.
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About: Accurate splice site predictor for a variety of genomes. Changes:Asp now supports three formats: -g fname for gff format -s fname for spf format -b dir for a binary format compatible with mGene. And a new switch -t which switches on a sigmoid-based transformation of the svm scores to get scores between 0 and 1.
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About: MultiBoost is a multi-purpose boosting package implemented in C++. It is based on the multi-class/multi-task AdaBoost.MH algorithm [Schapire-Singer, 1999]. Basic base learners (stumps, trees, products, Haar filters for image processing) can be easily complemented by new data representations and the corresponding base learners, without interfering with the main boosting engine. Changes:Initial Announcement on mloss.org.
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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: 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:
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About: A Python library that allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. Dynamically generates CPU and GPU modules for good performance. Deep Learning Tutorials illustrate deep learning with Theano. Changes:Initial Announcement on mloss.org.
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About: The scikit-learn aims to provide state of the art standard machine learning algorithms in Python. Changes:Initial Announcement on mloss.org.
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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: A Java library to create, process and manage mixtures of exponential families. Changes:Initial Announcement on mloss.org.
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About: MLPACK is the first comprehensive scalable machine learning library. Changes:Initial Announcement on mloss.org.
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