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A Library for Locally Weighted Projection RegressionStefan Klanke, Sethu Vijayakumar, Stefan Schaal; 9(Apr):623--626, 2008.
SharkChristian Igel, Verena Heidrich-Meisner, Tobias Glasmachers; 9(Jun):993--996, 2008.
LIBLINEAR: A Library for Large Linear ClassificationRong-En Fan, Kai-Wei Chang, Cho-Jui Hsieh, Xiang-Rui Wang, Chih-Jen Lin; 9(Aug):1871--1874, 2008.
JNCC2: The Java Implementation Of Naive Credal Classifier 2Giorgio Corani, Marco Zaffalon; 9(Dec):2695--2698, 2008.
Python Environment for Bayesian Learning: Inferring the Structure of Bayesian Networks from Knowledge and DataAbhik Shah, Peter Woolf; 10(Feb):159--162, 2009.
Nieme: Large-Scale Energy-Based ModelsFrancis Maes; 10(Mar):743--746, 2009.
Java-ML: A Machine Learning LibraryThomas Abeel, Yves Van de Peer, Yvan Saeys; 10(Apr):931--934, 2009.
Model Monitor (M2): Evaluating, Comparing, and Monitoring ModelsTroy Raeder, Nitesh V. Chawla; 10(Jul):1387--1390, 2009.
Dlib-ml: A Machine Learning ToolkitDavis E. King; 10(Jul):1755--1758, 2009.
RL-Glue: Language-Independent Software for Reinforcement-Learning ExperimentsBrian Tanner, Adam White; 10(Sep):2133--2136, 2009.
DL-Learner: Learning Concepts in Description LogicsJens Lehmann; 10(Nov):2639−2642, 2009.
Error-Correcting Output Codes LibrarySergio Escalera, Oriol Pujol, Petia Radeva; 11(Feb):661−664, 2010.
PyBrainTom Schaul, Justin Bayer, Daan Wierstra, Yi Sun, Martin Felder, Frank Sehnke, Thomas Rückstieß, Jürgen Schmidhuber; 11(Feb):743−746, 2010.
Continuous Time Bayesian Network Reasoning and Learning EngineChristian R. Shelton, Yu Fan, William Lam, Joon Lee, Jing Xu; 11(Mar):1137−1140, 2010.
SFO: A Toolbox for Submodular Function OptimizationAndreas Krause; 11(Mar):1141−1144, 2010.
MOA: Massive Online AnalysisAlbert Bifet, Geoff Holmes, Richard Kirkby, Bernhard Pfahringer; 11(May):1601−1604, 2010.
FastInf: An Efficient Approximate Inference LibraryAriel Jaimovich, Ofer Meshi, Ian McGraw, Gal Elidan; 11(May):1733−1736, 2010.
The SHOGUN Machine Learning ToolboxSören Sonnenburg, Gunnar Rätsch, Sebastian Henschel, Christian Widmer, Jonas Behr, Alexander Zien, Fabio de Bona, Alexander Binder, Christian Gehl, Vojtěch Franc; 11(Jun):1799−1802, 2010.
A Surrogate Modeling and Adaptive Sampling Toolbox for Computer Based DesignDirk Gorissen, Ivo Couckuyt, Piet Demeester, Tom Dhaene, Karel Crombecq; 11(Jul):2051−2055, 2010.
Model-based Boosting 2.0Torsten Hothorn, Peter Bühlmann, Thomas Kneib, Matthias Schmid, Benjamin Hofner; 11(Aug):2109−2113, 2010.
libDAI: A Free and Open Source C++ Library for Discrete Approximate Inference in Graphical ModelsJoris M. Mooij; 11(Aug):2169−2173, 2010.
Gaussian Processes for Machine Learning (GPML) ToolboxCarl Edward Rasmussen, Hannes Nickisch; 11(Nov):3011−3015, 2010.
CARP: Software for Fishing Out Good Clustering AlgorithmsVolodymyr Melnykov, Ranjan Maitra; 12(Jan):69−73, 2011.
The arules R-Package Ecosystem: Analyzing Interesting Patterns from Large Transaction Data SetsMichael Hahsler, Sudheer Chelluboina, Kurt Hornik, Christian Buchta; 12(Jun):2021−2025, 2011.
MSVMpack: A Multi-Class Support Vector Machine PackageFabien Lauer, Yann Guermeur; 12(Jul):2293−2296, 2011.
Waffles: A Machine Learning ToolkitMichael Gashler; 12(Jul):2383−2387, 2011.
MULAN: A Java Library for Multi-Label LearningGrigorios Tsoumakas, Eleftherios Spyromitros-Xioufis, Jozef Vilcek, Ioannis Vlahavas; 12(Jul):2411−2414, 2011.
LPmade: Link Prediction Made EasyRyan N. Lichtenwalter, Nitesh V. Chawla; 12(Aug):2489−2492, 2011.
Scikit-learn: Machine Learning in PythonFabian Pedregosa, Gaël Varoquaux, Alexandre Gramfort, Vincent Michel, Bertrand Thirion, Olivier Grisel, Mathieu Blondel, Peter Prettenhofer, Ron Weiss, Vincent Dubourg, Jake Vanderplas, Alexandre Passos, David Cournapeau, Matthieu Brucher, Matthieu Perrot, édouard Duchesnay; 12(Oct):2825−2830, 2011.
The Stationary Subspace Analysis ToolboxJan Saputra Müller, Paul von Bünau, Frank C. Meinecke, Franz J. Király, Klaus-Robert Müller; 12(Oct):3065−3069, 2011.
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