Entropy-based discretization methods for ranking data CR De Sá, C Soares, A Knobbe Information Sciences 329, 921-936, 2016 | 62 | 2016 |
An ensemble of autonomous auto-encoders for human activity recognition KD Garcia, CR de Sá, M Poel, T Carvalho, J Mendes-Moreira, ... Neurocomputing 439, 271-280, 2021 | 59 | 2021 |
Mining association rules for label ranking CR De Sá, C Soares, AM Jorge, P Azevedo, J Costa Advances in Knowledge Discovery and Data Mining: 15th Pacific-Asia …, 2011 | 56 | 2011 |
Label ranking forests CR Sá, C Soares, A Knobbe, P Cortez Expert Systems 34 (1), 2017 | 44 | 2017 |
Variance-based feature importance in neural networks CR de Sá International Conference on Discovery Science, 306-315, 2019 | 32 | 2019 |
Exceptional preferences mining C Rebelo de Sá, W Duivesteijn, C Soares, A Knobbe Discovery Science: 19th International Conference, DS 2016, Bari, Italy …, 2016 | 30 | 2016 |
Combining boosted trees with metafeature engineering for predictive maintenance V Cerqueira, F Pinto, C Sá, C Soares Advances in Intelligent Data Analysis XV: 15th International Symposium, IDA …, 2016 | 29 | 2016 |
Building robust models for Human Activity Recognition from raw accelerometers data using Gated Recurrent Units and Long Short Term Memory Neural Networks CRS Jeremiah Okai, Stylianos Paraschiakos, Marian Beekman, Arno Knobbe 41st Annual International Conference of the IEEE Engineering in Medicine and …, 2019 | 25 | 2019 |
Discovering a taste for the unusual: exceptional models for preference mining CR de Sá, W Duivesteijn, P Azevedo, AM Jorge, C Soares, A Knobbe Machine Learning 107, 1775-1807, 2018 | 25 | 2018 |
Multi-interval discretization of continuous attributes for label ranking CR De Sá, C Soares, A Knobbe, P Azevedo, AM Jorge International Conference on Discovery Science, 155-169, 2013 | 19 | 2013 |
Preference rules for label ranking: Mining patterns in multi-target relations CR de Sá, P Azevedo, C Soares, AM Jorge, A Knobbe Information Fusion 40, 112-125, 2018 | 14 | 2018 |
Distance-based decision tree algorithms for label ranking C Rebelo de Sá, C Rebelo, C Soares, A Knobbe Progress in Artificial Intelligence: 17th Portuguese Conference on …, 2015 | 13 | 2015 |
A recurrent neural network architecture to model physical activity energy expenditure in older people S Paraschiakos, CR de Sá, J Okai, PE Slagboom, M Beekman, A Knobbe Data Mining and Knowledge Discovery 36 (1), 477-512, 2022 | 12 | 2022 |
KnowBots: discovering relevant patterns in chatbot dialogues A Rivolli, C Amaral, L Guardão, CR de Sá, C Soares Discovery Science: 22nd International Conference, DS 2019, Split, Croatia …, 2019 | 7 | 2019 |
Mining exceptional social behaviour CC Jorge, M Atzmueller, BM Heravi, JL Gibson, CR de Sá, RJF Rossetti Progress in Artificial Intelligence: 19th EPIA Conference on Artificial …, 2019 | 7 | 2019 |
Building robust prediction models for defective sensor data using artificial neural networks CR de Sá, AK Shekar, H Ferreira, C Soares 14th International Conference on Soft Computing Models in Industrial and …, 2020 | 5 | 2020 |
“Want to come play with me?” Outlier subgroup discovery on spatio‐temporal interactions C Centeio Jorge, M Atzmueller, BM Heravi, JL Gibson, RJF Rossetti, ... Expert Systems 40 (5), e12686, 2023 | 4 | 2023 |
Ensemble clustering for novelty detection in data streams KD Garcia, ER de Faria, CR de Sá, J Mendes-Moreira, CC Aggarwal, ... Discovery Science: 22nd International Conference, DS 2019, Split, Croatia …, 2019 | 4 | 2019 |
Preference rules CR de Sá, C Soares, AM Jorge, PJ Azevedo, A Knobbe submitted to Information Fusion Journal, 2017 | 3 | 2017 |
Permutation tests for label ranking CR de Sá, C Soares, A Knobbe Proceedings of the 27th Benelux Conference on Artificial Intelligence (BNAIC …, 2015 | 2 | 2015 |