Sarah Vluymans
Title
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Cited by
Year
IFROWANN: imbalanced fuzzy-rough ordered weighted average nearest neighbor classification
E Ramentol, S Vluymans, N Verbiest, Y Caballero, R Bello, C Cornelis, ...
IEEE Transactions on Fuzzy Systems 23 (5), 1622-1637, 2014
712014
Multiple instance learning
F Herrera, S Ventura, R Bello, C Cornelis, A Zafra, D Sánchez-Tarragó, ...
Multiple instance learning, 17-33, 2016
702016
Fuzzy rough classifiers for class imbalanced multi-instance data
S Vluymans, DS Tarragó, Y Saeys, C Cornelis, F Herrera
Pattern Recognition 53, 36-45, 2016
432016
Applications of fuzzy rough set theory in machine learning: a survey
S Vluymans, L D’eer, Y Saeys, C Cornelis
Fundamenta Informaticae 142 (1-4), 53-86, 2015
392015
Evolutionary undersampling for imbalanced big data classification
I Triguero, M Galar, S Vluymans, C Cornelis, H Bustince, F Herrera, ...
2015 IEEE Congress on Evolutionary Computation (CEC), 715-722, 2015
342015
Multi-label classification using a fuzzy rough neighborhood consensus
S Vluymans, C Cornelis, F Herrera, Y Saeys
Information Sciences 433, 96-114, 2018
282018
Dynamic affinity-based classification of multi-class imbalanced data with one-versus-one decomposition: a fuzzy rough set approach
S Vluymans, A Fernández, Y Saeys, C Cornelis, F Herrera
Knowledge and Information Systems 56 (1), 55-84, 2018
262018
Learning from imbalanced data
S Vluymans
Dealing with Imbalanced and Weakly Labelled Data in Machine Learning using …, 2019
152019
EPRENNID: An evolutionary prototype reduction based ensemble for nearest neighbor classification of imbalanced data
S Vluymans, I Triguero, C Cornelis, Y Saeys
Neurocomputing 216, 596-610, 2016
152016
Improving nearest neighbor classification using ensembles of evolutionary generated prototype subsets
N Verbiest, S Vluymans, C Cornelis, N García-Pedrajas, Y Saeys
Applied Soft Computing 44, 75-88, 2016
112016
Fuzzy multi-instance classifiers
S Vluymans, DS Tarragó, Y Saeys, C Cornelis, F Herrera
IEEE Transactions on Fuzzy Systems 24 (6), 1395-1409, 2016
112016
Semi-supervised fuzzy-rough feature selection
R Jensen, S Vluymans, N Mac Parthaláin, C Cornelis, Y Saeys
Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing, 185-195, 2015
102015
Dealing with imbalanced and weakly labelled data in machine learning using fuzzy and rough set methods
S Vluymans
Springer International Publishing, 2019
92019
Weight selection strategies for ordered weighted average based fuzzy rough sets
S Vluymans, N Mac Parthaláin, C Cornelis, Y Saeys
Information Sciences 501, 155-171, 2019
72019
Fuzzy rough sets for self-labelling: An exploratory analysis
S Vluymans, N Mac Parthaláin, C Cornelis, Y Saeys
2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 931-938, 2016
52016
Distributed fuzzy rough prototype selection for big data regression
S Vluymans, H Asfoor, Y Saeys, C Cornelis, M Tolentino, A Teredesai, ...
2015 Annual Conference of the North American Fuzzy Information Processing …, 2015
52015
Instance selection for imbalanced data
S Vluymans, N Verbiest, C Cornelis, Y Saeys
WorkshopRough Sets: Theory and Applications (RST&A); held at the 2014 Joint …, 2014
52014
Multiple Instance Multiple Label Learning
F Herrera, S Ventura, R Bello, C Cornelis, A Zafra, D Sánchez-Tarragó, ...
Multiple Instance Learning, 209-230, 2016
42016
Multi-instance regression
F Herrera, S Ventura, R Bello, C Cornelis, A Zafra, D Sánchez-Tarragó, ...
Multiple Instance Learning, 127-140, 2016
42016
Unsupervised multiple instance learning
F Herrera, S Ventura, R Bello, C Cornelis, A Zafra, D Sánchez-Tarragó, ...
Multiple Instance Learning, 141-167, 2016
22016
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