| Bankruptcy prediction for small-and medium-sized companies using severely imbalanced datasets M Zoričák, P Gnip, P Drotár, V Gazda Economic Modelling 84, 165-176, 2020 | 108 | 2020 |
| Selective oversampling approach for strongly imbalanced data P Gnip, L Vokorokos, P Drotár PeerJ Computer Science 7, e604, 2021 | 62 | 2021 |
| Small-and medium-enterprises bankruptcy dataset P Drotár, P Gnip, M Zoričak, V Gazda Data in brief 25, 2019 | 16 | 2019 |
| Ensemble methods for strongly imbalanced data: bankruptcy prediction P Gnip, P Drotár 2019 IEEE 17th International Symposium on Intelligent Systems and …, 2019 | 11 | 2019 |
| Bankruptcy prediction using ensemble of autoencoders optimized by genetic algorithm R Kanász, P Gnip, M Zoričák, P Drotár PeerJ Computer Science 9, e1257, 2023 | 1 | 2023 |
| Stability analysis of WkNN feature selection P Bugata, P Gnip, P Drotár 2019 IEEE 13th International Symposium on Applied Computational Intelligence …, 2019 | 1 | 2019 |
| Single-class bankruptcy prediction based on the data from annual reports P Drotár, P Gnip, M Zoričak, V Gazda Intelligent Data Engineering and Automated Learning–IDEAL 2018: 19th …, 2018 | 1 | 2018 |
| Clash of titans on imbalanced data: TabNet vs XGBoost R Kanász, P Drotár, P Gnip, M Zoričák 2024 IEEE Conference on Artificial Intelligence (CAI), 320-325, 2024 | | 2024 |
| Predikcia úpadku spoločností s ručením obmedzeným využitím metód pre rozpoznanie odľahlých bodov P Gnip, M Zoričák, P Drotár Západočeská univerzita v Plzni, 2017 | | 2017 |
