Alberto Fernández Hilario

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Francisco HerreraProfessor Computer Science and AI, DaSCI Research Institute, Granada University, SpainE-mail confirmado em decsai.ugr.es
Salvador GarcíaFull Professor of Computer Science and Artificial Intelligence. University of Granada.E-mail confirmado em decsai.ugr.es
Mikel GalarAssociate Professor of Computer Science and Artificial Intelligence, Universidad Pública de NavarraE-mail confirmado em unavarra.es
Humberto BustinceProfessor of Computer Science, Universidad Publica de NavarraE-mail confirmado em unavarra.es
María José Del Jesus DíazAssociate professor of Computer Science, University of JaénE-mail confirmado em ujaen.es
Edurne BarrenecheaAssociate professor of Computer Science, Universidad Publica de NavarraE-mail confirmado em unavarra.es
Julián Luengo MartínAssociate Professor at University of GranadaE-mail confirmado em decsai.ugr.es
Victoria Lopez MoralesResearch Associate, Imperial College LondonE-mail confirmado em imperial.ac.uk
Ronaldo C. PratiAssociate Professor of Computer Science, Universidade Federal do ABCE-mail confirmado em ufabc.edu.br
Bartosz KrawczykAssistant Professor, Center for Imaging Science, Rochester Institute of Technology, USAE-mail confirmado em rit.edu
J. SanzAssistant Professor of Computer Science and Artificial Intelligence, Universidad Pública de NavarraE-mail confirmado em unavarra.es
Joaquin Derrac RusData ScientistE-mail confirmado em gresearch.co.uk
Jesus Alcala-FdezFull Professor of Computer Science and Artificial Intelligence, University of GranadaE-mail confirmado em decsai.ugr.es
Saleh AlshomraniKing Abdulaziz UniversityE-mail confirmado em kau.edu.sa
Jose M. BenitezFull Professor, Universidad de GranadaE-mail confirmado em decsai.ugr.es
Nitesh V Chawla, Fellow: ACM, IEEE,...Frank Freimann Professor of CSE.,Director, Lucy Family Institute for Data & Soc, Univ. of Notre DameE-mail confirmado em nd.edu
Isaac Triguero VelázquezDistinguished Senior Research Fellow at University of Granada, Associate Professor in Data ScienceE-mail confirmado em nottingham.ac.uk
Sara del Río GarcíaSystems engineer, RHEA Group for European Space AgencyE-mail confirmado em sciops.esa.int
Vasile PaladeProfessor of Artificial Intelligence and Data Science, Coventry UniversityE-mail confirmado em coventry.ac.uk
Pedro Henriques AbreuAssociate Professor, Department of Informatics Engineering, University of CoimbraE-mail confirmado em dei.uc.pt

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Alberto Fernández Hilario

Full Professor of Computer Science and Artificial Intelligence, University of Granada

E-mail confirmado em decsai.ugr.es - Página inicial

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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	3270	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	2957*	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	2278	2010
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	1915	2018
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	1895	2013
Learning from imbalanced data sets A Fernández, S García, M Galar, RC Prati, B Krawczyk, F Herrera Springer 10 (2018), 2018	1397	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	912	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	799	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	471	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	468	2013
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	374	2012
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	372	2008
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	350	2014
KEEL 3.0: an open source software for multi-stage analysis in data mining I Triguero, S González, JM Moyano, S García, J Alcalá-Fdez, J Luengo, ... International Journal of Computational Intelligence Systems 10 (1), 1238-1249, 2017	290	2017
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	275	2015
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	271	2017
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	253	2019
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	236	2009
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	233	2011
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	215	2010

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