Alberto Fernández

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Francisco HerreraProfessor Computer Science and AI, Granada University, SpainVerified email at decsai.ugr.es
Salvador GarcíaFull Professor of Computer Science and Artificial Intelligence. University of Granada.Verified email at decsai.ugr.es
Mikel GalarAssociate Professor of Computer Science and Artificial Intelligence, Universidad Pública de NavarraVerified email at unavarra.es
Humberto BustinceProfessor of Computer Science, Universidad Publica de NavarraVerified email at unavarra.es
María José Del Jesus DíazAssociate professor of Computer Science, University of JaénVerified email at ujaen.es
Edurne BarrenecheaAssociate professor of Computer Science, Universidad Publica de NavarraVerified email at unavarra.es
Julián Luengo MartínAssociate Professor at University of GranadaVerified email at decsai.ugr.es
Victoria Lopez MoralesResearch Associate, Imperial College LondonVerified email at imperial.ac.uk
J. SanzAssistant Professor of Computer Science and Artificial Intelligence, Universidad Pública de NavarraVerified email at unavarra.es
Joaquin Derrac RusData ScientistVerified email at gresearch.co.uk
Jesus Alcala-FdezAssociate Professor of Computer Science and Artificial Intelligence, University of GranadaVerified email at decsai.ugr.es
Saleh AlshomraniKing Abdulaziz UniversityVerified email at kau.edu.sa
Jose M. BenitezFull Professor, Universidad de GranadaVerified email at decsai.ugr.es
Nitesh V ChawlaFrank Freimann Professor of Computer Science & Engg., Notre DameVerified email at nd.edu
Isaac Triguero VelázquezDistinguished Senior Research Fellow at University of Granada, Associate Professor in Data ScienceVerified email at nottingham.ac.uk
Sara del Río GarcíaSystems engineer, RHEA Group for European Space AgencyVerified email at sciops.esa.int
Vasile PaladeProfessor of Artificial Intelligence and Data Science, Coventry UniversityVerified email at coventry.ac.uk
Mikel ElkanoNeuraptic AIVerified email at neuraptic.ai
Cristóbal J CarmonaAssociate Professor at University of JaenVerified email at ujaen.es
Daniel PeraltaPostdoctoral researcher - Doctor Assistant, Department of Information Technology. Ghent UniversityVerified email at ugent.be

Alberto Fernández

Associate Professor in Computer Science and Artificial Intelligence, University of Granada

Verified email at decsai.ugr.es - Homepage

Explainable Artificial Intelligence Data Science Big Data Bioinformatics Computational Intelligence


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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	2725	2012
KEEL data-mining software tool: data set repository, integration of algorithms and experimental analysis framework J Alcalá-Fdez, A Fernández, J Luengo, J Derrac, ... Journal of Multiple-Valued Logic and Soft Computing 17 (2-3), 255-287, 2011	2635*	2011
Advanced nonparametric tests for multiple comparisons in the design of experiments in computational intelligence and data mining: Experimental analysis of power S García, A Fernández, J Luengo, F Herrera Information sciences 180 (10), 2044-2064, 2010	1942	2010
An insight into classification with imbalanced data: Empirical results and current trends on using data intrinsic characteristics V López, A Fernández, S García, V Palade, F Herrera Information sciences 250, 113-141, 2013	1589	2013
SMOTE for Learning from Imbalanced Data: Progress and Challenges, Marking the 15-year Anniversary A Fernandez, S Garcia, F Herrera, NV Chawla Journal of Artificial Intelligence Research 61, 863-905, 2018	1064	2018
Learning from imbalanced data sets A Fernández, S García, M Galar, RC Prati, B Krawczyk, F Herrera Springer 10, 978-3, 2018	867	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	781	2011
A study of statistical techniques and performance measures for genetics-based machine learning: accuracy and interpretability S García, A Fernández, J Luengo, F Herrera Soft Computing 13, 959-977, 2009	726	2009
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	414	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, 2013	409	2013
A study of the behaviour of linguistic fuzzy rule based classification systems in the framework of imbalanced data-sets A Fernández, S García, MJ del Jesus, F Herrera Fuzzy Sets and Systems 159 (18), 2378-2398, 2008	337	2008
Analysis of preprocessing vs. cost-sensitive learning for imbalanced classification. Open problems on intrinsic data characteristics V López, A Fernández, JG Moreno-Torres, F Herrera Expert Systems with Applications 39 (7), 6585-6608, 2012	335	2012
Big Data with Cloud Computing: an insight on the computing environment, MapReduce, and programming frameworks A Fernández, S del Río, V López, A Bawakid, MJ del Jesus, JM Benítez, ... Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 4 (5 …, 2014	314	2014
On the combination of genetic fuzzy systems and pairwise learning for improving detection rates on intrusion detection systems S Elhag, A Fernández, A Bawakid, S Alshomrani, F Herrera Expert Systems with Applications 42 (1), 193-202, 2015	238	2015
KEEL 3.0: an open source software for multi-stage analysis in data mining I Triguero, S González, JM Moyano, S García López, J Alcalá Fernández, ... Atlantis Press, 2017	231	2017
An insight into imbalanced Big Data classification: outcomes and challenges A Fernández, S del Río, NV Chawla, F Herrera Complex & Intelligent Systems 3, 105-120, 2017	212	2017
Hierarchical fuzzy rule based classification systems with genetic rule selection for imbalanced data-sets A Fernández, MJ del Jesus, F Herrera International Journal of Approximate Reasoning 50 (3), 561-577, 2009	208	2009
Genetics-based machine learning for rule induction: state of the art, taxonomy, and comparative study A Fernández, S García, J Luengo, E Bernadó-Mansilla, F Herrera IEEE Transactions on Evolutionary Computation 14 (6), 913-941, 2010	197	2010
Addressing data complexity for imbalanced data sets: analysis of SMOTE-based oversampling and evolutionary undersampling J Luengo, A Fernández, S García, F Herrera Soft Computing-A Fusion of Foundations, Methodologies and Applications 15 …, 2011	190	2011
Evolutionary fuzzy systems for explainable artificial intelligence: Why, when, what for, and where to? A Fernandez, F Herrera, O Cordon, MJ del Jesus, F Marcelloni IEEE Computational intelligence magazine 14 (1), 69-81, 2019	180	2019

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