Mikel Galar

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Humberto BustinceProfessor of Computer Science, Universidad Publica de NavarraDirección de correo verificada de unavarra.es
Francisco HerreraProfessor Computer Science and AI, DaSCI Research Institute, Granada University, SpainDirección de correo verificada de decsai.ugr.es
Alberto Fernández HilarioFull Professor of Computer Science and Artificial Intelligence, University of GranadaDirección de correo verificada de decsai.ugr.es
Edurne BarrenecheaAssociate professor of Computer Science, Universidad Publica de NavarraDirección de correo verificada de unavarra.es
J. SanzAssistant Professor of Computer Science and Artificial Intelligence, Universidad Pública de NavarraDirección de correo verificada de unavarra.es
Daniel PaternainDepartment of Statistics, Computer Science and MathematicsDirección de correo verificada de unavarra.es
Bartosz KrawczykAssistant Professor, Center for Imaging Science, Rochester Institute of Technology, USADirección de correo verificada de rit.edu
Ronaldo C. PratiAssociate Professor of Computer Science, Universidade Federal do ABCDirección de correo verificada de ufabc.edu.br
Mikel ElkanoNeuraptic AIDirección de correo verificada de neuraptic.ai
Isaac Triguero VelázquezDistinguished Senior Research Fellow at University of Granada, Associate Professor in Data ScienceDirección de correo verificada de ugr.es
Salvador GarcíaFull Professor of Computer Science and Artificial Intelligence. University of Granada.Dirección de correo verificada de decsai.ugr.es
Carlos Lopez-MolinaUniversidad Publica de NavarraDirección de correo verificada de unavarra.es
Miguel PagolaUniversidad Pública de NavarraDirección de correo verificada de unavarra.es
Javier Fernandez FernandezUniversidad Pública de NavarraDirección de correo verificada de unavarra.es
Aranzazu JurioPhD., Universidad Publica de NavarraDirección de correo verificada de unavarra.es
Jose M. BenitezFull Professor, Universidad de GranadaDirección de correo verificada de decsai.ugr.es
Radko MesiarSTU Bratislava, Slovakia, Faculty of Civil Engineering, Dept. Mathematics and Descriptive GeometryDirección de correo verificada de math.sk
José A. SáezDept. of Statistics and Operations Research, University of GranadaDirección de correo verificada de ugr.es
Mikel UrizUniversidad pública de NavarraDirección de correo verificada de unavarra.es
Daniel PeraltaAssistant Professor, Dept. of Computer Science and Artificial Intelligence, University of GranadaDirección de correo verificada de ugr.es

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Mikel Galar

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

Dirección de correo verificada de unavarra.es - Página principal

Artificial Intelligence Data Mining Machine Learning Classification Ensembles


Título Ordenar por citas Ordenar por año Ordenar por título	Citado por Citado por	Año
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	3361	2012
Learning from imbalanced data sets A Fernández, S García, M Galar, RC Prati, B Krawczyk, F Herrera Springer 10 (2018), 2018	1501	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	932	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	485	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	478	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	297	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	217	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	203	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	190	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	181	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	170	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	140	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	137	2016
Cost-sensitive learning A Fernández, S García, M Galar, RC Prati, B Krawczyk, F Herrera, ... Learning from imbalanced data sets, 63-78, 2018	122	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	113	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	113	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	110	2015
Dynamic ensemble selection for multi-class classification with one-class classifiers B Krawczyk, M Galar, M Woźniak, H Bustince, F Herrera Pattern Recognition 83, 34-51, 2018	107	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	105	2018
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	103	2018

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