Alberto Fernández Hilario

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Francisco HerreraProfessor Computer Science and AI, DaSCI Research Institute, Granada University, SpainEmail confirmado em decsai.ugr.es
Salvador GarcíaFull Professor of Computer Science and Artificial Intelligence. University of Granada.Email confirmado em decsai.ugr.es
Mikel GalarAssociate Professor of Computer Science and Artificial Intelligence, Universidad Pública de NavarraEmail confirmado em unavarra.es
Humberto BustinceProfessor of Computer Science, Universidad Publica de NavarraEmail confirmado em unavarra.es
María José Del Jesus DíazAssociate professor of Computer Science, University of JaénEmail confirmado em ujaen.es
Edurne BarrenecheaAssociate professor of Computer Science, Universidad Publica de NavarraEmail confirmado em unavarra.es
Julián Luengo MartínAssociate Professor at University of GranadaEmail confirmado em decsai.ugr.es
Victoria Lopez MoralesResearch Associate, Imperial College LondonEmail confirmado em imperial.ac.uk
J. SanzAssistant Professor of Computer Science and Artificial Intelligence, Universidad Pública de NavarraEmail confirmado em unavarra.es
Joaquin Derrac RusData ScientistEmail confirmado em gresearch.co.uk
Ronaldo C. PratiAssociate Professor of Computer Science, Universidade Federal do ABCEmail confirmado em ufabc.edu.br
Bartosz KrawczykAssistant Professor, Center for Imaging Science, Rochester Institute of Technology, USAEmail confirmado em rit.edu
Jesus Alcala-FdezFull Professor of Computer Science and Artificial Intelligence, University of GranadaEmail confirmado em decsai.ugr.es
Saleh AlshomraniKing Abdulaziz UniversityEmail confirmado em kau.edu.sa
Jose M. BenitezFull Professor, Universidad de GranadaEmail 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 DameEmail confirmado em nd.edu
Isaac Triguero VelázquezDistinguished Senior Research Fellow at University of Granada, Associate Professor in Data ScienceEmail confirmado em nottingham.ac.uk
Sara del Río GarcíaSystems engineer, RHEA Group for European Space AgencyEmail confirmado em sciops.esa.int
Vasile PaladeProfessor of Artificial Intelligence and Data Science, Coventry UniversityEmail confirmado em coventry.ac.uk
Pedro Henriques AbreuAssociate Professor, Department of Informatics Engineering, University of CoimbraEmail confirmado em dei.uc.pt

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Alberto Fernández Hilario

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

Email 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	3272	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	2967*	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	2282	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	1935	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	1899	2013
Learning from imbalanced data sets A Fernández Springer, 2018	1403	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	915	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	803	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	469	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	373	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	291	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	277	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	256	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	235	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	216	2010

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