Orange NMF is an add-on for Orange data mining software package.
Orange is open source, data mining software based on Python and C++ programming. A useful component of Orange allows for a drag and drop interface to visualize building the data processing flow and analysis pipeline, or visual programming. On the canvas of this modular program, analysis or processing objects called “widgets” are dropped and connected to create a simple yet powerful data processing flow.
In this project, the Orange-NMF add on makes two popular matrix factorization methods available in Orange; non-negative matrix factorization (NMF), and robust singular value decomposition, (rSVD). To support these matrix factorization widgets, pre- and post- data processing widgets are included in the module. The pre-processing widgets are designed to deal with normalizations, missing data, etc. The post-processing widgets are designed to view and assess the results of the matrix factorization.
Documentation is found at:
Widgets: Fajwel Fogel (Ecole Polytechnique ParisTech)
All the NMF methods call NIMFA library, implemented by Marinka Zitnik (Bioinformatics Laboratory, FRI UL).
Thanks also to
Doug Marsteller, Stan Young (NISS), Chris Beecher, Paul Fogel.