Machine Learning Open Source Software

原文链接http://jmlr.csail.mit.edu/mloss/

JMLR上面的开源软件

To support the open
source software movement, JMLR MLOSS publishes contributions related to implementations of non-trivial machine learning algorithms, toolboxes or even languages for scientific computing. Submission instructions are available here.

A Library for Locally Weighted Projection RegressionStefan
Klanke, Sethu Vijayakumar, Stefan Schaal; 9(Apr):623--626, 2008.

[abs][pdf] [code][mloss.org]

SharkChristian
Igel, Verena Heidrich-Meisner, Tobias Glasmachers; 9(Jun):993--996, 2008.

[abs][pdf] [code][mloss.org]

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.

[abs][pdf] [code][mloss.org]

JNCC2: The Java Implementation Of Naive Credal Classifier 2Giorgio
Corani, Marco Zaffalon; 9(Dec):2695--2698, 2008.

[abs][pdf] [code][mloss.org]

Python Environment for Bayesian Learning: Inferring the Structure of Bayesian Networks from Knowledge and DataAbhik
Shah, Peter Woolf; 10(Feb):159--162, 2009.

[abs][pdf] [code][mloss.org]

Nieme: Large-Scale Energy-Based ModelsFrancis
Maes; 10(Mar):743--746, 2009.

[abs][pdf] [code][mloss.org]

Java-ML: A Machine Learning LibraryThomas
Abeel, Yves Van de Peer, Yvan Saeys; 10(Apr):931--934, 2009.

[abs][pdf] [code][mloss.org]

Model Monitor (M2):
Evaluating, Comparing, and Monitoring ModelsTroy Raeder, Nitesh
V. Chawla; 10(Jul):1387--1390, 2009.

[abs][pdf] [code][mloss.org]

Dlib-ml: A Machine Learning ToolkitDavis
E. King; 10(Jul):1755--1758, 2009.

[abs][pdf] [code][mloss.org]

RL-Glue: Language-Independent Software for Reinforcement-Learning ExperimentsBrian
Tanner, Adam White; 10(Sep):2133--2136, 2009.

[abs][pdf] [code][mloss.org]

DL-Learner: Learning Concepts in Description LogicsJens
Lehmann; 10(Nov):2639−2642, 2009.

[abs][pdf] [code][mloss.org]

Error-Correcting Output Codes LibrarySergio
Escalera, Oriol Pujol, Petia Radeva; 11(Feb):661−664, 2010.

[abs][pdf] [code][mloss.org]

PyBrainTom
Schaul, Justin Bayer, Daan Wierstra, Yi Sun, Martin Felder, Frank Sehnke, Thomas Rückstieß, Jürgen Schmidhuber; 11(Feb):743−746, 2010.

[abs][pdf] [code][mloss.org]

Continuous Time Bayesian Network Reasoning and Learning EngineChristian
R. Shelton, Yu Fan, William Lam, Joon Lee, Jing Xu; 11(Mar):1137−1140, 2010.

[abs][pdf] [code][mloss.org]

SFO: A Toolbox for Submodular Function OptimizationAndreas
Krause; 11(Mar):1141−1144, 2010.

[abs][pdf] [code][mloss.org]

MOA: Massive Online AnalysisAlbert
Bifet, Geoff Holmes, Richard Kirkby, Bernhard Pfahringer; 11(May):1601−1604, 2010.

[abs][pdf] [code][mloss.org]

FastInf: An Efficient Approximate Inference LibraryAriel
Jaimovich, Ofer Meshi, Ian McGraw, Gal Elidan; 11(May):1733−1736, 2010.

[abs][pdf] [code][mloss.org]

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.

[abs][pdf] [code][mloss.org]

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.

[abs][pdf] [code][mloss.org]

Model-based Boosting 2.0Torsten
Hothorn, Peter Bühlmann, Thomas Kneib, Matthias Schmid, Benjamin Hofner; 11(Aug):2109−2113, 2010.

[abs][pdf] [code][mloss.org]

libDAI: A Free and Open Source C++ Library for Discrete Approximate Inference in Graphical ModelsJoris
M. Mooij; 11(Aug):2169−2173, 2010.

[abs][pdf] [code][mloss.org]

Gaussian Processes for Machine Learning (GPML) ToolboxCarl
Edward Rasmussen, Hannes Nickisch; 11(Nov):3011−3015, 2010.

[abs][pdf] [code][mloss.org]

CARP: Software for Fishing Out Good Clustering AlgorithmsVolodymyr
Melnykov, Ranjan Maitra; 12(Jan):69−73, 2011.

[abs][pdf] [code][mloss.org]

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.

[abs][pdf] [code][mloss.org]

MSVMpack: A Multi-Class Support Vector Machine PackageFabien
Lauer, Yann Guermeur; 12(Jul):2293−2296, 2011.

[abs][pdf] [code][mloss.org]

Waffles: A Machine Learning ToolkitMichael
Gashler; 12(Jul):2383−2387, 2011.

[abs][pdf] [code][mloss.org]

MULAN: A Java Library for Multi-Label LearningGrigorios
Tsoumakas, Eleftherios Spyromitros-Xioufis, Jozef Vilcek, Ioannis Vlahavas; 12(Jul):2411−2414, 2011.

[abs][pdf] [code][mloss.org]

LPmade: Link Prediction Made EasyRyan
N. Lichtenwalter, Nitesh V. Chawla; 12(Aug):2489−2492, 2011.

[abs][pdf] [code][mloss.org]

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.

[abs][pdf] [code][mloss.org]

The Stationary Subspace Analysis ToolboxJan
Saputra Müller, Paul von Bünau, Frank C. Meinecke, Franz J. Király, Klaus-Robert Müller; 12(Oct):3065−3069, 2011.

[abs][pdf] [code][mloss.org]