Ensemble learning for data stream analysis: A survey B Krawczyk, LL Minku, J Gama, J Stefanowski, M Woźniak Information Fusion 37, 132-156, 2017 | 1054 | 2017 |
SMOTE–IPF: Addressing the noisy and borderline examples problem in imbalanced classification by a re-sampling method with filtering JA Sáez, J Luengo, J Stefanowski, F Herrera Information Sciences 291, 184-203, 2015 | 594 | 2015 |
Incomplete information tables and rough classification J Stefanowski, A Tsoukias Computational intelligence 17 (3), 545-566, 2001 | 540 | 2001 |
Reacting to different types of concept drift: The accuracy updated ensemble algorithm D Brzezinski, J Stefanowski IEEE transactions on neural networks and learning systems 25 (1), 81-94, 2013 | 527 | 2013 |
On the extension of rough sets under incomplete information J Stefanowski, A Tsoukiàs New Directions in Rough Sets, Data Mining, and Granular-Soft Computing: 7th …, 1999 | 442 | 1999 |
Lingo: Search results clustering algorithm based on singular value decomposition S Osiński, J Stefanowski, D Weiss Intelligent Information Processing and Web Mining: Proceedings of the …, 2004 | 424 | 2004 |
Open challenges for data stream mining research G Krempl, I Žliobaite, D Brzeziński, E Hüllermeier, M Last, V Lemaire, ... ACM SIGKDD explorations newsletter 16 (1), 1-10, 2014 | 377 | 2014 |
On rough set based approaches to induction of decision rules J Stefanowski Rough sets in knowledge discovery 1 (1), 500-529, 1998 | 360 | 1998 |
Local neighbourhood extension of SMOTE for mining imbalanced data T Maciejewski, J Stefanowski 2011 IEEE symposium on computational intelligence and data mining (CIDM …, 2011 | 322 | 2011 |
Types of minority class examples and their influence on learning classifiers from imbalanced data K Napierala, J Stefanowski Journal of Intelligent Information Systems 46, 563-597, 2016 | 294 | 2016 |
Learning from imbalanced data in presence of noisy and borderline examples K Napierała, J Stefanowski, S Wilk Rough Sets and Current Trends in Computing: 7th International Conference …, 2010 | 279 | 2010 |
Selective pre-processing of imbalanced data for improving classification performance J Stefanowski, S Wilk International conference on data warehousing and knowledge discovery, 283-292, 2008 | 242 | 2008 |
ROSE-software implementation of the rough set theory B Predki, R Słowiński, J Stefanowski, R Susmaga, S Wilk Rough Sets and Current Trends in Computing: First International Conference …, 1998 | 239 | 1998 |
Variable consistency model of dominance-based rough sets approach S Greco, B Matarazzo, R Slowinski, J Stefanowski Rough Sets and Current Trends in Computing: Second International Conference …, 2001 | 230 | 2001 |
An algorithm for induction of decision rules consistent with the dominance principle S Greco, B Matarazzo, R Slowinski, J Stefanowski Rough Sets and Current Trends in Computing: Second International Conference …, 2001 | 225 | 2001 |
Neighbourhood sampling in bagging for imbalanced data J Błaszczyński, J Stefanowski Neurocomputing 150, 529-542, 2015 | 219 | 2015 |
Accuracy updated ensemble for data streams with concept drift D Brzeziński, J Stefanowski International conference on hybrid artificial intelligence systems, 155-163, 2011 | 206 | 2011 |
Combining block-based and online methods in learning ensembles from concept drifting data streams D Brzezinski, J Stefanowski Information Sciences 265, 50-67, 2014 | 204 | 2014 |
Rough classification in incomplete information systems R SLOWIŃSKI, J Stefanowski Models and Methods in Multiple Criteria Decision Making, 1347-1357, 1989 | 193 | 1989 |
Three discretization methods for rule induction JW Grzymala‐Busse, J Stefanowski International Journal of Intelligent Systems 16 (1), 29-38, 2001 | 149 | 2001 |