Mikel Galar

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Humberto BustinceProfessor of Computer Science, Universidad Publica de NavarraVerified email at unavarra.es
Francisco HerreraProfessor Computer Science and AI, Granada University, SpainVerified email at decsai.ugr.es
Alberto FernándezFull Professor in Computer Science and Artificial Intelligence, University of GranadaVerified email at decsai.ugr.es
Edurne BarrenecheaAssociate professor of Computer Science, Universidad Publica de NavarraVerified email at unavarra.es
J. SanzAssistant Professor of Computer Science and Artificial Intelligence, Universidad Pública de NavarraVerified email at unavarra.es
Bartosz KrawczykAssistant Professor, Center for Imaging Science, Rochester Institute of Technology, USAVerified email at rit.edu
Daniel PaternainDepartment of Statistics, Computer Science and MathematicsVerified email at unavarra.es
Ronaldo C. PratiAssociate Professor of Computer Science, Universidade Federal do ABCVerified email at ufabc.edu.br
Mikel ElkanoNeuraptic AIVerified email at neuraptic.ai
Isaac Triguero VelázquezDistinguished Senior Research Fellow at University of Granada, Associate Professor in Data ScienceVerified email at nottingham.ac.uk
Carlos Lopez-MolinaUniversidad Publica de NavarraVerified email at unavarra.es
Salvador GarcíaFull Professor of Computer Science and Artificial Intelligence. University of Granada.Verified email at decsai.ugr.es
Miguel PagolaUniversidad Pública de NavarraVerified email at unavarra.es
Javier FernandezUniversidad Pública de NavarraVerified email at unavarra.es
Aranzazu JurioPhD., Universidad Publica de NavarraVerified email at unavarra.es
Daniel PeraltaPostdoctoral researcher - Doctor Assistant, Department of Information Technology. Ghent UniversityVerified email at ugent.be
Jose M. BenitezFull Professor, Universidad de GranadaVerified email at decsai.ugr.es
José A. SáezDept. of Statistics and Operations Research, University of GranadaVerified email at ugr.es
Radko MesiarSTU Bratislava, Slovakia, Faculty of Civil Engineering, Dept. Mathematics and Descriptive GeometryVerified email at math.sk
Julián Luengo MartínAssociate Professor at University of GranadaVerified email at decsai.ugr.es

Mikel Galar

Associate Professor of Computer Science and Artificial Intelligence, Universidad Pública de Navarra

Verified email at unavarra.es - Homepage

Artificial Intelligence Data Mining Machine Learning Classification Ensembles


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A Review on Ensembles for the Class Imbalance Problem: Bagging-, Boosting-, and Hybrid-Based Approaches M Galar, A Fernández, E Barrenechea, H Bustince, F Herrera Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE …, 2012	2857	2012
Learning from imbalanced data sets A Fernández, S García, M Galar, RC Prati, B Krawczyk, F Herrera Springer 10, 978-3, 2018	991	2018
An overview of ensemble methods for binary classifiers in multi-class problems: Experimental study on one-vs-one and one-vs-all schemes M Galar, A Fernández, E Barrenechea, H Bustince, F Herrera Pattern Recognition 44 (8), 1761-1776, 2011	803	2011
EUSBoost: Enhancing ensembles for highly imbalanced data-sets by evolutionary undersampling M Galar, A Fernández, E Barrenechea, F Herrera Pattern recognition 46 (12), 3460-3471, 2013	430	2013
Analysing the classification of imbalanced data-sets with multiple classes: Binarization techniques and ad-hoc approaches A Fernández, V López, M Galar, M José del Jesus, F Herrera Knowledge-Based Systems 42, 97-110, 2013	417	2013
Evolutionary undersampling boosting for imbalanced classification of breast cancer malignancy B Krawczyk, M Galar, Ł Jeleń, F Herrera Applied Soft Computing 38, 714-726, 2016	254	2016
A new approach to interval-valued Choquet integrals and the problem of ordering in interval-valued fuzzy sets applications H Bustince, M Galar, B Bedregal, A Kolesarova, R Mesiar IEEE Transactions on Fuzzy Systems, 2013	207	2013
A survey on fingerprint minutiae-based local matching for verification and identification: Taxonomy and experimental evaluation D Peralta, M Galar, I Triguero, D Paternain, S García, E Barrenechea, ... Information Sciences 315, 67-87, 2015	180	2015
Medical diagnosis of cardiovascular diseases using an interval-valued fuzzy rule-based classification system JA Sanz, M Galar, A Jurio, A Brugos, M Pagola, H Bustince Applied Soft Computing 20, 103-111, 2014	179	2014
Enhancing Multiclass Classification in FARC-HD Fuzzy Classifier: On the Synergy Between-Dimensional Overlap Functions and Decomposition Strategies M Elkano, M Galar, JA Sanz, A Fernández, E Barrenechea, F Herrera, ... IEEE Transactions on Fuzzy Systems 23 (5), 1562-1580, 2014	164	2014
Analyzing the presence of noise in multi-class problems: alleviating its influence with the one-vs-one decomposition JA Sáez, M Galar, J Luengo, F Herrera Knowledge and information systems 38, 179-206, 2014	155	2014
Tackling the problem of classification with noisy data using multiple classifier systems: Analysis of the performance and robustness JA Sáez, M Galar, J Luengo, F Herrera Information Sciences 247, 1-20, 2013	125	2013
Fuzzy Rule-Based Classification Systems for multi-class problems using binary decomposition strategies: On the influence of n-dimensional overlap functions in the … M Elkano, M Galar, J Sanz, H Bustince Information Sciences 332, 94-114, 2016	118	2016
Dynamic classifier selection for one-vs-one strategy: avoiding non-competent classifiers M Galar, A Fernández, E Barrenechea, H Bustince, F Herrera Pattern Recognition 46 (12), 3412-3424, 2013	112	2013
DRCW-OVO: distance-based relative competence weighting combination for one-vs-one strategy in multi-class problems M Galar, A Fernández, E Barrenechea, F Herrera Pattern recognition 48 (1), 28-42, 2015	102	2015
CHI-BD: A fuzzy rule-based classification system for Big Data classification problems M Elkano, M Galar, J Sanz, H Bustince Fuzzy Sets and Systems 348, 75-101, 2018	95	2018
Consensus via penalty functions for decision making in ensembles in fuzzy rule-based classification systems M Elkano, M Galar, JA Sanz, PF Schiavo, S Pereira Jr, GP Dimuro, ... Applied Soft Computing 67, 728-740, 2018	95	2018
INFFC: An iterative class noise filter based on the fusion of classifiers with noise sensitivity control JA Sáez, M Galar, J Luengo, F Herrera Information Fusion 27, 19-32, 2016	95	2016
Ordering-based pruning for improving the performance of ensembles of classifiers in the framework of imbalanced datasets M Galar, A Fernández, E Barrenechea, H Bustince, F Herrera Information Sciences 354, 178-196, 2016	90	2016
A survey of fingerprint classification Part I: Taxonomies on feature extraction methods and learning models M Galar, J Derrac, D Peralta, I Triguero, D Paternain, C Lopez-Molina, ... Knowledge-based systems 81, 76-97, 2015	89	2015

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