Machine Learning Open Source Software

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 Regression

Stefan Klanke, Sethu Vijayakumar, Stefan Schaal; 9(Apr):623--626, 2008. 
[abs][pdf]    [code][mloss.org]

Shark

Christian Igel, Verena Heidrich-Meisner, Tobias Glasmachers; 9(Jun):993--996, 2008. 
[abs][pdf]    [code][mloss.org]

LIBLINEAR: A Library for Large Linear Classification

Rong-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 2

Giorgio 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 Data

Abhik Shah, Peter Woolf; 10(Feb):159--162, 2009. 
[abs][pdf]    [code][mloss.org]

Nieme: Large-Scale Energy-Based Models

Francis Maes; 10(Mar):743--746, 2009. 
[abs][pdf]    [code][mloss.org]

Java-ML: A Machine Learning Library

Thomas Abeel, Yves Van de Peer, Yvan Saeys; 10(Apr):931--934, 2009. 
[abs][pdf]    [code][mloss.org]

Model Monitor (M²): Evaluating, Comparing, and Monitoring Models

Troy Raeder, Nitesh V. Chawla; 10(Jul):1387--1390, 2009. 
[abs][pdf]    [code][mloss.org]

Dlib-ml: A Machine Learning Toolkit

Davis E. King; 10(Jul):1755--1758, 2009. 
[abs][pdf]    [code][mloss.org]

RL-Glue: Language-Independent Software for Reinforcement-Learning Experiments

Brian Tanner, Adam White; 10(Sep):2133--2136, 2009. 
[abs][pdf]    [code][mloss.org]

DL-Learner: Learning Concepts in Description Logics

Jens Lehmann; 10(Nov):2639−2642, 2009. 
[abs][pdf]    [code][mloss.org]

Error-Correcting Output Codes Library

Sergio Escalera, Oriol Pujol, Petia Radeva; 11(Feb):661−664, 2010. 
[abs][pdf]    [code][mloss.org]

PyBrain

Tom 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 Engine

Christian 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 Optimization

Andreas Krause; 11(Mar):1141−1144, 2010. 
[abs][pdf]    [code][mloss.org]

MOA: Massive Online Analysis

Albert Bifet, Geoff Holmes, Richard Kirkby, Bernhard Pfahringer; 11(May):1601−1604, 2010. 
[abs][pdf]    [code][mloss.org]

FastInf: An Efficient Approximate Inference Library

Ariel Jaimovich, Ofer Meshi, Ian McGraw, Gal Elidan; 11(May):1733−1736, 2010. 
[abs][pdf]    [code][mloss.org]

The SHOGUN Machine Learning Toolbox

Sören 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 Design

Dirk Gorissen, Ivo Couckuyt, Piet Demeester, Tom Dhaene, Karel Crombecq; 11(Jul):2051−2055, 2010. 
[abs][pdf]    [code][mloss.org]

Model-based Boosting 2.0

Torsten 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 Models

Joris M. Mooij; 11(Aug):2169−2173, 2010. 
[abs][pdf]    [code][mloss.org]

Gaussian Processes for Machine Learning (GPML) Toolbox

Carl Edward Rasmussen, Hannes Nickisch; 11(Nov):3011−3015, 2010. 
[abs][pdf]    [code][mloss.org]

CARP: Software for Fishing Out Good Clustering Algorithms

Volodymyr 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 Sets

Michael Hahsler, Sudheer Chelluboina, Kurt Hornik, Christian Buchta; 12(Jun):2021−2025, 2011. 
[abs][pdf]    [code][mloss.org]

MSVMpack: A Multi-Class Support Vector Machine Package

Fabien Lauer, Yann Guermeur; 12(Jul):2293−2296, 2011. 
[abs][pdf]    [code][mloss.org]

Waffles: A Machine Learning Toolkit

Michael Gashler; 12(Jul):2383−2387, 2011. 
[abs][pdf]    [code][mloss.org]

MULAN: A Java Library for Multi-Label Learning

Grigorios Tsoumakas, Eleftherios Spyromitros-Xioufis, Jozef Vilcek, Ioannis Vlahavas; 12(Jul):2411−2414, 2011. 
[abs][pdf]    [code][mloss.org]

LPmade: Link Prediction Made Easy

Ryan N. Lichtenwalter, Nitesh V. Chawla; 12(Aug):2489−2492, 2011. 
[abs][pdf]    [code][mloss.org]

Scikit-learn: Machine Learning in Python

Fabian 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 Toolbox

Jan Saputra Müller, Paul von Bünau, Frank C. Meinecke, Franz J. Király, Klaus-Robert Müller; 12(Oct):3065−3069, 2011. 
[abs][pdf]    [code][mloss.org]

MULTIBOOST: A Multi-purpose Boosting Package

Djalel Benbouzid, Róbert Busa-Fekete, Norman Casagrande, François-David Collin, Balázs Kégl; 13(Mar):549−553, 2012. 
[abs][pdf]    [code][mloss.org]

ML-Flex: A Flexible Toolbox for Performing Classification Analyses In Parallel

Stephen R. Piccolo, Lewis J. Frey; 13(Mar):555−559, 2012. 
[abs][pdf]    [code][sourceforge.net]

GPLP: A Local and Parallel Computation Toolbox for Gaussian Process Regression

Chiwoo Park, Jianhua Z. Huang, Yu Ding; 13(Mar):775−779, 2012. 
[abs][pdf]    [code][mloss.org]

NIMFA : A Python Library for Nonnegative Matrix Factorization

Marinka Žitnik, Blaž Zupan; 13(Mar):849−853, 2012. 
[abs][pdf]    [code][mloss.org]

The huge Package for High-dimensional Undirected Graph Estimation in R

Tuo Zhao, Han Liu, Kathryn Roeder, John Lafferty, Larry Wasserman; 13(Apr):1059−1062, 2012. 
[abs][pdf]    [code][cran.r-project.org]

glm-ie: Generalised Linear Models Inference & Estimation Toolbox

Hannes Nickisch; 13(May):1699−1703, 2012. 
[abs][pdf]    [code][mloss.org]

Jstacs: A Java Framework for Statistical Analysis and Classification of Biological Sequences

Jan Grau, Jens Keilwagen, André Gohr, Berit Haldemann, Stefan Posch, Ivo Grosse; 13(Jun):1967−1971, 2012. 
[abs][pdf]    [code][mloss.org]

Pattern for Python

Tom De Smedt, Walter Daelemans; 13(Jun):2063−2067, 2012. 
[abs][pdf]    [code][mloss.org]

DEAP: Evolutionary Algorithms Made Easy

Félix-Antoine Fortin, François-Michel De Rainville, Marc-André Gardner, Marc Parizeau, Christian Gagné; 13(Jul):2171−2175, 2012. 
[abs][pdf]    [code][deap.gel.ulaval.ca]

A Topic Modeling Toolbox Using Belief Propagation

Jia Zeng; 13(Jul):2233−2236, 2012. 
[abs][pdf]    [code][mloss.org]

PREA: Personalized Recommendation Algorithms Toolkit

Joonseok Lee, Mingxuan Sun, Guy Lebanon; 13(Sep):2699−2703, 2012. 
[abs][pdf]    [code][mloss.org]

Oger: Modular Learning Architectures For Large-Scale Sequential Processing

David Verstraeten, Benjamin Schrauwen, Sander Dieleman, Philemon Brakel, Pieter Buteneers, Dejan Pecevski; 13(Oct):2995−2998, 2012. 
[abs][pdf]    [code][mloss.org]

Sally: A Tool for Embedding Strings in Vector Spaces

Konrad Rieck, Christian Wressnegger, Alexander Bikadorov; 13(Nov):3247−3251, 2012. 
[abs][pdf]    [code][mloss.org]

DARWIN: A Framework for Machine Learning and Computer Vision Research and Development

Stephen Gould; 13(Dec):3533−3537, 2012. 
[abs][pdf]    [code][mloss.org]

SVDFeature: A Toolkit for Feature-based Collaborative Filtering

Tianqi Chen, Weinan Zhang, Qiuxia Lu, Kailong Chen, Zhao Zheng, Yong Yu; 13(Dec):3619−3622, 2012. 
[abs][pdf]    [code][mloss.org]

A C++ Template-Based Reinforcement Learning Library: Fitting the Code to the Mathematics

Hervé Frezza-Buet, Matthieu Geist; 14(Feb):625−628, 2013. 
[abs][pdf]    [code][malis.metz.supelec.fr]

MLPACK: A Scalable C++ Machine Learning Library

Ryan R. Curtin, James R. Cline, N. P. Slagle, William B. March, Parikshit Ram, Nishant A. Mehta, Alexander G. Gray; 14(Mar):801−805, 2013. 
[abs][pdf]    [code][mloss.org]

GPstuff: Bayesian Modeling with Gaussian Processes

Jarno Vanhatalo, Jaakko Riihimäki, Jouni Hartikainen, Pasi Jylänki, Ville Tolvanen, Aki Vehtari; 14(Apr):1175−1179, 2013. 
[abs][pdf]    [code][mloss.org]

JKernelMachines: A Simple Framework for Kernel Machines

David Picard, Nicolas Thome, Matthieu Cord; 14(May):1417−1421, 2013. 
[abs][pdf][bib]    [code][mloss.org]

Orange: Data Mining Toolbox in Python

Janez Demšar, Tomaž Curk, Aleš Erjavec, Črt Gorup, Tomaž Hočevar, Mitar Milutinovič, Martin Možina, Matija Polajnar, Marko Toplak, Anže Starič, Miha Štajdohar, Lan Umek, Lan Žagar, Jure Žbontar, Marinka Žitnik, Blaž Zupan; 14(Aug):2349−2353, 2013. 
[abs][pdf][bib]    [code][mloss.org]

Tapkee: An Efficient Dimension Reduction Library

Sergey Lisitsyn, Christian Widmer, Fernando J. Iglesias Garcia; 14(Aug):2355−2359, 2013. 
[abs][pdf][bib]    [code][mloss.org]

The CAM Software for Nonnegative Blind Source Separation in R-Java

Niya Wang, Fan Meng, Li Chen, Subha Madhavan, Robert Clarke, Eric P. Hoffman, Jianhua Xuan, Yue Wang; 14(Sep):2899−2903, 2013.
[abs][pdf][bib]    [code][mloss.org]

QuantMiner for Mining Quantitative Association Rules

Ansaf Salleb-Aouissi, Christel Vrain, Cyril Nortet, Xiangrong Kong, Vivek Rathod, Daniel Cassard; 14(Oct):3153−3157, 2013. 
[abs][pdf][bib]    [code][github.com]

Divvy: Fast and Intuitive Exploratory Data Analysis

Joshua M. Lewis, Virginia R. de Sa, Laurens van der Maaten; 14(Oct):3159−3163, 2013. 
[abs][pdf][bib]    [code][mloss.org]

GURLS: A Least Squares Library for Supervised Learning

Andrea Tacchetti, Pavan K. Mallapragada, Matteo Santoro, Lorenzo Rosasco; 14(Oct):3201−3205, 2013. 
[abs][pdf][bib]    [code][github.com]