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]
