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Sarah Vluymans
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Multiple instance learning
F Herrera, S Ventura, R Bello, C Cornelis, A Zafra, D Sánchez-Tarragó, ...
Multiple instance learning: foundations and algorithms, 17-33, 2016
1552016
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
1172014
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
862015
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
722015
Multi-label classification using a fuzzy rough neighborhood consensus
S Vluymans, C Cornelis, F Herrera, Y Saeys
Information Sciences 433, 96-114, 2018
632018
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
632016
Learning from imbalanced data
S Vluymans, S Vluymans
Dealing with Imbalanced and Weakly Labelled Data in Machine Learning using …, 2019
592019
Dealing with imbalanced and weakly labelled data in machine learning using fuzzy and rough set methods
S Vluymans
Springer 107, 236, 2019
462019
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, 55-84, 2018
462018
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
442019
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
292016
Fuzzy multi-instance classifiers
S Vluymans, DS Tarragó, Y Saeys, C Cornelis, F Herrera
IEEE Transactions on Fuzzy Systems 24 (6), 1395-1409, 2016
172016
Semi-supervised fuzzy-rough feature selection
R Jensen, S Vluymans, NM Parthaláin, C Cornelis, Y Saeys
Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing: 15th …, 2015
152015
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
132016
Learning from Imbalanced Data In IEEE Transactions on Knowledge and Data Engineering
S Vluymans
IEEE: New York, NY, USA, 1263-1284, 2009
122009
Multi-instance regression
F Herrera, S Ventura, R Bello, C Cornelis, A Zafra, D Sánchez-Tarragó, ...
Multiple Instance Learning: Foundations and Algorithms, 127-140, 2016
102016
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
102015
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
72014
Multiple Instance Multiple Label Learning
F Herrera, S Ventura, R Bello, C Cornelis, A Zafra, D Sánchez-Tarragó, ...
Multiple Instance Learning: Foundations and Algorithms, 209-230, 2016
52016
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
42016
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Artikelen 1–20