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Efficient algorithms for finding optimal binary features in numeric and nominal labeled data

, , , , and . Knowledge and Information Systems, 42 (2): 465--492 (2015)

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Diverse Subgroup Set Discovery, and . Data Mining and Knowledge Discovery, 25 (2): 208--242 (2012)Subgroup Discovery Meets Bayesian Network -- An Exceptional Model Mining Approach, , , and . IEEE Int'l Conference on Data Mining, (2010)Exceptional model mining, , and . Data Mining and Knowledge Discovery, 30 (1): 47--98 (2016)Efficient algorithms for finding optimal binary features in numeric and nominal labeled data, , , , and . Knowledge and Information Systems, 42 (2): 465--492 (2015)From local patterns to global models: The lego approach to data mining, , , and . From local patterns to global models: proceedings of the ECML PKDD 2008 Workshop, page 1--16. Citeseer, (2008)Cost-based quality measures in subgroup discovery, , , and . Journal of Intelligent Information Systems, 45 (3): 337--355 (2015)Preference rules for label ranking: Mining patterns in multi-target relations., , , , and . CoRR, (2019)Distance-Based Decision Tree Algorithms for Label Ranking., , , and . EPIA, volume 9273 of Lecture Notes in Computer Science, page 525-534. Springer, (2015)Biclustering Multivariate Time Series., , and . IDA, volume 10584 of Lecture Notes in Computer Science, page 27-39. Springer, (2017)Efficient Algorithms for Finding Richer Subgroup Descriptions in Numeric and Nominal Data., , , and . ICDM, page 499-508. IEEE Computer Society, (2012)