| Ensemble learning for data stream analysis: A survey B Krawczyk, LL Minku, J Gama, J Stefanowski, M Woźniak Information Fusion 37, 132-156, 2017 | 1276 | 2017 |
| A survey of multiple classifier systems as hybrid systems M Woźniak, M Grana, E Corchado Information Fusion 16, 3-17, 2014 | 1204 | 2014 |
| A survey on data preprocessing for data stream mining: Current status and future directions S Ramírez-Gallego, B Krawczyk, S García, M Woźniak, F Herrera Neurocomputing 239, 39-57, 2017 | 634 | 2017 |
| Cost-sensitive decision tree ensembles for effective imbalanced classification B Krawczyk, M Woźniak, G Schaefer Applied Soft Computing 14, 554-562, 2014 | 465 | 2014 |
| Analyzing the oversampling of different classes and types of examples in multi-class imbalanced datasets JA Sáez, B Krawczyk, M Woźniak Pattern Recognition 57, 164-178, 2016 | 319 | 2016 |
| Advanced Machine Learning techniques for fake news (online disinformation) detection: A systematic mapping study M Choraś, K Demestichas, A Giełczyk, Á Herrero, P Ksieniewicz, ... Applied Soft Computing, 2021 | 184 | 2021 |
| Clustering-based ensembles for one-class classification B Krawczyk, M Woźniak, B Cyganek Information sciences 264, 182-195, 2014 | 181 | 2014 |
| Combined Cleaning and Resampling Algorithm for Multi-Class Imbalanced Data with Label Noise M Koziarski, M Woźniak, B Krawczyk Knowledge-Based Systems 204 (arXiv preprint arXiv:2004.03406), 106223, 2020 | 175 | 2020 |
| Radial-based oversampling for noisy imbalanced data classification M Koziarski, B Krawczyk, M Woźniak Neurocomputing 343, 19-33, 2019 | 171 | 2019 |
| Radial-based oversampling for multiclass imbalanced data classification B Krawczyk, M Koziarski, M Woźniak IEEE transactions on neural networks and learning systems 31 (8), 2818-2831, 2019 | 142 | 2019 |
| Monotonic classification: An overview on algorithms, performance measures and data sets JR Cano, PA Gutiérrez, B Krawczyk, M Woźniak, S García Neurocomputing 341, 168-182, 2019 | 132 | 2019 |
| CCR: A combined cleaning and resampling algorithm for imbalanced data classification M Koziarski, M Woźniak International Journal of Applied Mathematics and Computer Science 27 (4), 2017 | 129 | 2017 |
| Preprocessed dynamic classifier ensemble selection for highly imbalanced drifted data streams P Zyblewski, R Sabourin, M Wozniak Information Fusion 66 (https://doi.org/10.1016/j.inffus.2020.09), 138-154, 2021 | 121 | 2021 |
| One-class classifiers with incremental learning and forgetting for data streams with concept drift B Krawczyk, M Woźniak Soft Computing 19 (12), 3387-3400, 2015 | 119 | 2015 |
| How to design the fair experimental classifier evaluation K Stapor, P Ksieniewicz, S García, M Woźniak Applied Soft Computing 104, 107219, 2021 | 118 | 2021 |
| Dynamic ensemble selection for multi-class classification with one-class classifiers B Krawczyk, M Galar, M Woźniak, H Bustince, F Herrera Pattern Recognition 83, 34-51, 2018 | 106 | 2018 |
| Fault diagnosis of marine 4-stroke diesel engines using a one-vs-one extreme learning ensemble J Kowalski, B Krawczyk, M Woźniak Engineering Applications of Artificial Intelligence 57, 134-141, 2017 | 98 | 2017 |
| Sentiment analysis for fake news detection by means of neural networks S Kula, M Choraś, R Kozik, P Ksieniewicz, M Woźniak 20th International Conference on Computational Science, ICCS 2020 12140 …, 2020 | 97 | 2020 |
| Nearest neighbor classification for high-speed big data streams using spark S Ramírez-Gallego, B Krawczyk, S García, M Woźniak, JM Benítez, ... IEEE Transactions on Systems, Man, and Cybernetics: Systems 47 (10), 2727-2739, 2017 | 92 | 2017 |
| On the usefulness of one-class classifier ensembles for decomposition of multi-class problems B Krawczyk, M Woźniak, F Herrera Pattern Recognition 48 (12), 3969-3982, 2015 | 92 | 2015 |
Bartosz KrawczykAssistant Professor, Center for Imaging Science, Rochester Institute of Technology, USAVerified email at rit.edu
