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Hess/Morik/2017a: C-SALT: Mining Class-Specific ALTerations in Boolean Matrix Factorization

Bibtype Inproceedings
Bibkey Hess/Morik/2017a
Author Hess, Sibylle and Morik, Katharina
Title C-SALT: Mining Class-Specific ALTerations in Boolean Matrix Factorization
Booktitle Joint European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2017
Publisher Springer
Abstract Given labeled data represented by a binary matrix, we consider the task to derive a Boolean matrix factorization which identifies commonalities and specifications among the classes. While existing works focus on rank-one factorizations which are either specific or common to the classes, we derive class-specific alterations from common factorizations as well. Therewith, we broaden the applicability of our new method to datasets whose class-dependencies have a more complex structure. On the basis of synthetic and real-world datasets, we show on the one hand that our method is able to filter structure which corresponds to our model assumption, and on the other hand that our model assumption is justified in real-world application.
Our method is parameter-free.
Year 2017
Projekt SFB876-C1
Url https://link.springer.com/content/pdf/10.1007/978-3-319-71249-9_33.pdf
hess_morik_2017a.pdf [1632 KB]
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