| Multi-criteria classification–a new scheme for application of dominance-based decision rules J Błaszczyński, S Greco, R Słowiński European Journal of Operational Research 181 (3), 1030-1044, 2007 | 263 | 2007 |
| Sequential covering rule induction algorithm for variable consistency rough set approaches J Błaszczyński, R Słowiński, M Szeląg Information Sciences 181 (5), 987-1002, 2011 | 253 | 2011 |
| Neighbourhood sampling in bagging for imbalanced data J Błaszczyński, J Stefanowski Neurocomputing 150, 529-542, 2015 | 220 | 2015 |
| Monotonic variable consistency rough set approaches J Błaszczyński, S Greco, R Słowiński, M Szelg International journal of approximate reasoning 50 (7), 979-999, 2009 | 180 | 2009 |
| A green chemistry-based classification model for the synthesis of silver nanoparticles M Cinelli, SR Coles, MN Nadagouda, J Błaszczyński, R Słowiński, ... Green Chemistry 17 (5), 2825-2839, 2015 | 106 | 2015 |
| Learning ensemble classifiers for diabetic retinopathy assessment E Saleh, J Błaszczyński, A Moreno, A Valls, P Romero-Aroca, ... Artificial intelligence in medicine 85, 50-63, 2018 | 102 | 2018 |
| Comparative analysis of targeted metabolomics: dominance-based rough set approach versus orthogonal partial least square-discriminant analysis H Blasco, J Błaszczyński, JC Billaut, L Nadal-Desbarats, PF Pradat, ... Journal of Biomedical Informatics 53, 291-299, 2015 | 94 | 2015 |
| 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 | 90 | 2010 |
| jMAF-Dominance-based rough set data analysis framework J Błaszczyński, S Greco, B Matarazzo, R Słowiński, M Szela̧g Rough Sets and Intelligent Systems-Professor Zdzisław Pawlak in Memoriam …, 2013 | 88 | 2013 |
| Auto loan fraud detection using dominance-based rough set approach versus machine learning methods J Błaszczyński, AT de Almeida Filho, A Matuszyk, M Szeląg, R Słowiński Expert Systems with Applications 163, 113740, 2021 | 86 | 2021 |
| Inductive discovery of laws using monotonic rules J BŁaszczyński, S Greco, R SŁowiński Engineering Applications of Artificial Intelligence 25 (2), 284-294, 2012 | 81 | 2012 |
| Incremental induction of decision rules from dominance-based rough approximations J Błaszczyński, R Słowiński Electronic Notes in Theoretical Computer Science 82 (4), 40-51, 2003 | 74 | 2003 |
| Extending bagging for imbalanced data J Błaszczyński, J Stefanowski, Ł Idkowiak Proceedings of the 8th international conference on computer recognition …, 2013 | 51 | 2013 |
| On variable consistency dominance-based rough set approaches J Błaszczyński, S Greco, R Słowiński, M Szeląg Rough Sets and Current Trends in Computing: 5th International Conference …, 2006 | 42 | 2006 |
| Robustness analysis of a green chemistry-based model for the classification of silver nanoparticles synthesis processes M Cinelli, SR Coles, MN Nadagouda, J Błaszczyński, R Słowiński, ... Journal of cleaner production 162, 938-948, 2017 | 37 | 2017 |
| Antimicrobial Activity and SAR Study of New Gemini Imidazolium‐Based Chlorides Ł Pałkowski, J Błaszczyński, A Skrzypczak, J Błaszczak, K Kozakowska, ... Chemical Biology & Drug Design 83 (3), 278-288, 2014 | 33 | 2014 |
| Variable consistency bagging ensembles J Błaszczyński, R Słowiński, J Stefanowski Transactions on Rough Sets XI, 40-52, 2010 | 28 | 2010 |
| Rule-based estimation of attribute relevance J Błaszczyński, R Słowiński, R Susmaga Rough Sets and Knowledge Technology: 6th International Conference, RSKT 2011 …, 2011 | 27 | 2011 |
| Empirical risk minimization for dominance-based rough set approaches Y Kusunoki, J Błaszczyński, M Inuiguchi, R Słowiński Information Sciences 567, 395-417, 2021 | 23 | 2021 |
| Local data characteristics in learning classifiers from imbalanced data J Błaszczyński, J Stefanowski Advances in Data Analysis with Computational Intelligence Methods: Dedicated …, 2018 | 23 | 2018 |
Roman SlowinskiPoznan University of Technology在 cs.put.poznan.pl 的电子邮件经过验证
