Alberto Fernández Hilario

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Francisco HerreraProfessor Computer Science and AI, DaSCI Research Institute, 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
Ronaldo C. PratiAssociate Professor of Computer Science, Universidade Federal do ABCVerified email at ufabc.edu.br
Bartosz KrawczykAssistant Professor, Center for Imaging Science, Rochester Institute of Technology, USAVerified email at rit.edu
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-FdezFull 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 Chawla, Fellow: ACM, IEEE,...Frank Freimann Professor of CSE.,Director, Lucy Family Institute for Data & Soc, Univ. of 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
Pedro Henriques AbreuAssociate Professor, Department of Informatics Engineering, University of CoimbraVerified email at dei.uc.pt

Alberto Fernández Hilario

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

Verified email at decsai.ugr.es - Homepage

Trustworthy AI XAI Machine Learning Data Science


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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	3228	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	2932*	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	2256	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	1865	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	1847	2018
Learning from imbalanced data sets A Fernández, S García, M Galar, RC Prati, B Krawczyk, F Herrera Springer 10 (2018), 2018	1358	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	896	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	792	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	465	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	464	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	372	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	370	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	348	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	287	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	273	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	262	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	247	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	234	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	230	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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