| Integrating selective pre-processing of imbalanced data with ivotes ensemble J Błaszczyński, M Deckert, J Stefanowski, S Wilk Rough Sets and Current Trends in Computing: 7th International Conference …, 2010 | 91 | 2010 |
| Batch weighted ensemble for mining data streams with concept drift M Deckert Foundations of Intelligent Systems: 19th International Symposium, ISMIS 2011 …, 2011 | 35 | 2011 |
| Incremental rule-based learners for handling concept drift: an overview M Deckert Foundations of Computing and Decision Sciences 38 (1), 35-65, 2013 | 21 | 2013 |
| Ensembles of abstaining classifiers based on rule sets J Błaszczyński, J Stefanowski, M Zając International symposium on methodologies for intelligent systems, 382-391, 2009 | 17 | 2009 |
| RILL: algorithm for learning rules from streaming data with concept drift M Deckert, J Stefanowski Foundations of Intelligent Systems: 21st International Symposium, ISMIS 2014 …, 2014 | 13 | 2014 |
| Comparing block ensembles for data streams with concept drift M Deckert, J Stefanowski New Trends in Databases and Information Systems, 69-78, 2013 | 10 | 2013 |
| IIvotes ensemble for imbalanced data J Błaszczyński, M Deckert, J Stefanowski, S Wilk Intelligent Data Analysis 16 (5), 777-801, 2012 | 10 | 2012 |
| Online batch weighted ensemble for mining data streams with concept drift M Deckert W Proceedings of the New Frontiers in Mining Complex Patterns Workshop, ECML …, 2013 | 2 | 2013 |
| Przyrostowe uczenie reguł oraz wykorzystanie detekcji zmian w blokowych klasyfikatorach złożonych do przetwarzania danych strumieniowych MA Deckert | | 2015 |
| Przyrostowe uczenie reguª oraz wykorzystanie detekcji zmian w blokowych klasyfikatorach zªo» onych do przetwarzania danych strumieniowych M Deckert | | |
