A systematic review of data mining and machine learning for air pollution epidemiology C Bellinger, MS Mohomed Jabbar, O Zaïane, A Osornio-Vargas BMC public health 17, 1-19, 2017 | 254 | 2017 |
One-class versus binary classification: Which and when? C Bellinger, S Sharma, N Japkowicz 2012 11th international conference on machine learning and applications 2 …, 2012 | 114 | 2012 |
Synthetic oversampling with the majority class: A new perspective on handling extreme imbalance S Sharma, C Bellinger, B Krawczyk, O Zaiane, N Japkowicz 2018 IEEE international conference on data mining (ICDM), 447-456, 2018 | 105 | 2018 |
Roadmap on machine learning in electronic structure HJ Kulik, T Hammerschmidt, J Schmidt, S Botti, MAL Marques, M Boley, ... Electronic Structure 4 (2), 023004, 2022 | 103 | 2022 |
Manifold-based synthetic oversampling with manifold conformance estimation C Bellinger, C Drummond, N Japkowicz Machine Learning 107, 605-637, 2018 | 68 | 2018 |
Smotefuna: Synthetic minority over-sampling technique based on furthest neighbour algorithm AS Tarawneh, ABA Hassanat, K Almohammadi, D Chetverikov, ... IEEE Access 8, 59069-59082, 2020 | 64 | 2020 |
Framework for extreme imbalance classification: SWIM—sampling with the majority class C Bellinger, S Sharma, N Japkowicz, OR Zaïane Knowledge and Information Systems 62, 841-866, 2020 | 51 | 2020 |
Anomaly detection in gamma ray spectra: A machine learning perspective S Sharma, C Bellinger, N Japkowicz, R Berg, K Ungar 2012 IEEE symposium on computational intelligence for security and defence …, 2012 | 43 | 2012 |
Synthetic oversampling for advanced radioactive threat detection C Bellinger, N Japkowicz, C Drummond 2015 IEEE 14th International Conference on Machine Learning and Applications …, 2015 | 40 | 2015 |
Beyond the boundaries of smote: A framework for manifold-based synthetically oversampling C Bellinger, C Drummond, N Japkowicz Machine Learning and Knowledge Discovery in Databases: European Conference …, 2016 | 35 | 2016 |
Active learning for one-class classification V Barnabé-Lortie, C Bellinger, N Japkowicz 2015 IEEE 14th international conference on machine learning and applications …, 2015 | 34 | 2015 |
Interdisciplinary-driven hypotheses on spatial associations of mixtures of industrial air pollutants with adverse birth outcomes J Serrano-Lomelin, CC Nielsen, MSM Jabbar, O Wine, C Bellinger, ... Environment international 131, 104972, 2019 | 27 | 2019 |
Sampling a longer life: Binary versus one-class classification revisited C Bellinger, S Sharma, OR Zaıane, N Japkowicz First International Workshop on Learning with Imbalanced Domains: Theory and …, 2017 | 27 | 2017 |
Undersampling with support vectors for multi-class imbalanced data classification B Krawczyk, C Bellinger, R Corizzo, N Japkowicz 2021 International Joint Conference on Neural Networks (IJCNN), 1-7, 2021 | 20 | 2021 |
Explainable image analysis for decision support in medical healthcare R Corizzo, Y Dauphin, C Bellinger, E Zdravevski, N Japkowicz 2021 IEEE international conference on big data (big data), 4667-4674, 2021 | 19 | 2021 |
The class imbalance problem in deep learning K Ghosh, C Bellinger, R Corizzo, P Branco, B Krawczyk, N Japkowicz Machine Learning, 1-57, 2022 | 18 | 2022 |
Active Measure Reinforcement Learning for Observation Cost Minimization. C Bellinger, R Coles, M Crowley, I Tamblyn Canadian Conference on AI, 2021 | 18 | 2021 |
Multi-label classification of anemia patients C Bellinger, A Amid, N Japkowicz, H Victor 2015 IEEE 14th International Conference on Machine Learning and Applications …, 2015 | 18 | 2015 |
Clustering based one-class classification for compliance verification of the comprehensive nuclear-test-ban treaty S Sharma, C Bellinger, N Japkowicz Advances in Artificial Intelligence: 25th Canadian Conference on Artificial …, 2012 | 17 | 2012 |
Calibrated resampling for imbalanced and long-tails in deep learning C Bellinger, R Corizzo, N Japkowicz Discovery Science: 24th International Conference, DS 2021, Halifax, NS …, 2021 | 15 | 2021 |