BMaD – Boolean Matrix Decomposition

The goal of a Boolean matrix decomposition (BMD) is to represent a given Boolean matrix as a product of two or more Boolean factor matrices. It is a well-known and researched problem with a wide range of applications, e.g. in multi-label classification, clustering, bioinformatics, or pattern mining.

The BMaD library is available at Github.


Wicker, Jörg; Hua, Yan Cathy; Rebello, Rayner; Pfahringer, Bernhard

XOR-based Boolean Matrix Decomposition Inproceedings

Wang, Jianyong; Shim, Kyuseok; Wu, Xindong (Ed.): 2019 IEEE International Conference on Data Mining (ICDM), pp. 638-647, IEEE, 2019, ISBN: 978-1-7281-4604-1.

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Tyukin, Andrey; Kramer, Stefan; Wicker, Jörg

BMaD -- A Boolean Matrix Decomposition Framework Inproceedings

Calders, Toon; Esposito, Floriana; Hüllermeier, Eyke; Meo, Rosa (Ed.): Machine Learning and Knowledge Discovery in Databases, pp. 481-484, Springer Berlin Heidelberg, 2014, ISBN: 978-3-662-44844-1.

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Wicker, Jörg; Pfahringer, Bernhard; Kramer, Stefan

Multi-label Classification Using Boolean Matrix Decomposition Inproceedings

Proceedings of the 27th Annual ACM Symposium on Applied Computing, pp. 179–186, ACM, 2012, ISBN: 978-1-4503-0857-1.

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