Jerzy (Jurek) Błaszczyński

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Roman SlowinskiPoznan University of TechnologyVerified email at cs.put.poznan.pl
Marcin SzelągInstitute of Computing Science, Poznan University of TechnologyVerified email at cs.put.poznan.pl
Jerzy StefanowskiPoznan University of TechnologyVerified email at cs.put.poznan.pl
Salvatore GrecoUniversità di CataniaVerified email at unict.it
Łukasz PałkowskiNicolaus Copernicus UniversityVerified email at cm.umk.pl
Szymon WilkAssociate Professor, Institute of Computing Science, Poznan University of TechnologyVerified email at cs.put.poznan.pl
Marco CinelliAssistant Professor, Leiden University, Decision Engineering for SustaInability and REsilienceVerified email at luc.leidenuniv.nl
Mallikarjuna NadagoudaUS EPAVerified email at epa.gov
Stuart R ColesUniversity of WarwickVerified email at warwick.ac.uk
Rajender S. VarmaU. S. Environmental Protection Agency, Center for Environmental Solutions and Emergency ResponseVerified email at epa.gov
Wojciech KotłowskiPoznan University of TechnologyVerified email at cs.put.poznan.pl
Magdalena DeckertPoznan University of Technology, Institute of Computing ScienceVerified email at cs.put.poznan.pl
Masahiro InuiguchiProfessor, Osaka UniversityVerified email at sys.es.osaka-u.ac.jp
Krzysztof DembczyńskiPoznan University of TechnologyVerified email at cs.put.poznan.pl
Cezary MazurekPoznan Supercomputing and Networking CenterVerified email at man.poznan.pl
Maciej KarolakCollegium Medicum im. L. Rydygiera w Bydgoszczy, Uniwerystet Mikołaja Kopernika w ToruniuVerified email at cm.umk.pl
Aida VallsUniversitat Rovira i VirgiliVerified email at urv.net
Antonio MorenoUniversitat Rovira i Virgili (URV)Verified email at urv.cat
Emran SalehUniversitat Rovira i VirgiliVerified email at urv.cat
Pedro Romero-ArocaHospital Universitari Sant JoanVerified email at urv.cat

Jerzy (Jurek) Błaszczyński

Poznań University of Technology

Verified email at cs.put.poznan.pl - Homepage

machine learning preference learning multicriteria decision analysis ensemble classifiers learning from imbalanced data


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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	260	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	251	2011
Neighbourhood sampling in bagging for imbalanced data J Błaszczyński, J Stefanowski Neurocomputing 150, 529-542, 2015	215	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	178	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	103	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	97	2018
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	89	2010
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	88	2015
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	84	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	82	2021
Inductive discovery of laws using monotonic rules J BŁaszczyński, S Greco, R SŁowiński Engineering Applications of Artificial Intelligence 25 (2), 284-294, 2012	80	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	73	2003
Extending bagging for imbalanced data J Błaszczyński, J Stefanowski, Ł Idkowiak Proceedings of the 8th international conference on computer recognition …, 2013	49	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	43	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	32	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	26	2011
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
Empirical risk minimization for dominance-based rough set approaches Y Kusunoki, J Błaszczyński, M Inuiguchi, R Słowiński Information Sciences 567, 395-417, 2021	22	2021

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