Publicaciones

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Conference Paper
A first study on the use of fuzzy rule based classification systems for problems with imbalanced data sets, del Jesus, M. J., Fernández A., García S., and Herrera F. , Proceedings of the Symposium on Fuzzy Systems in Computer Science (FSCS), September, Magdeburg (Germany), p.63-72, (2006)
A Pareto Based Ensemble with Feature and Instance Selection for Learning from Multi-Class Imbalanced Datasets, Fernández, A., Carmona C. J., del Jesus M. J., and Herrera F. , Proc. of the XVIII Conferencia de la Asociación Española para la Inteligencia Artificial (XVIII CAEPIA), p.1316-1317, (2018) PDF icon 2018 - CAEPIA-262.pdf (63.54 KB)
A proposal of Evolutionary Prototype Selection for Class Imbalance Problems, García, S., Cano J. R., Fernández A., and Herrera F. , Proceedings of the 7th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL), Volume 4224, p.1415-1423, (2006)
A study on the Use of the Fuzzy Reasoning Method based on the Winning Rule Vs. Voting Procedure for Classification with Imbalanced Data Sets, Fernández, A., García S., del Jesus M. J., and Herrera F. , Proceedings of the 9th International Work-Conference on Artificial Neural Networks (IWANN), June, San Sebastián (Spain), p.375-382, (2007)
Addressing Data-Complexity for Imbalanced Data-sets: A Preliminary Study on the Use of Preprocessing for C4.5, Luengo, J., Fernández A., Herrera F., and García S. , 9th International Conference on Intelligent Systems Designs and Applications (ISDA), p.523-528, (2009)
An Analysis of the Rule Weights and Fuzzy Reasoning Methods for Linguistic Rule Based Classification Systems Applied to Problems with Highly Imbalanced Data Sets, Fernández, A., García S., del Jesus M. J., and Herrera F. , International Workshop on Fuzzy Logic and Applications (WILF), July, Genova (Italy), p.170-179, (2007)
Analysing the Hierarchical Fuzzy Rule Based Classification Systems with Genetic Rule Selection, Fernández, A., del Jesus M. J., and Herrera F. , 4th International Workshop on Genetic and Evolutionary Fuzzy Systems (GEFS), March, Mieres (Spain), p.69-74, (2010)
Genetic Cooperative-Competitive Fuzzy Rule Based Learning Method using Genetic Programming for Highly Imbalanced Data-Sets, Fernández, A., Berlanga F. J., del Jesus M. J., and Herrera F. , 13 th International Fuzzy Systems Association World Congress and 6th European Society for Fuzzy Logic and Tecnology Conference (IFSA-EUSFLAT), Lisbon (Portugal), p.42-47, (2009)
Improving the Performance of Fuzzy Rule Based Classification Systems for Highly Imbalanced Data-sets Using an Evolutionary Adaptive Inference System, Fernández, A., del Jesus M. J., and Herrera F. , 10th International Work-Conference on Artificial Neural Networks (IWANN), June, Volume 5517, Salamanca (Spain), p.294-301,, (2009)
KEEL: A Data Mining Software Tool Integrating Genetic Fuzzy Systems, Alcalá-Fdez, J., García S., Berlanga F. J., Fernández A., Sánchez L., del Jesus M. J., and Herrera F. , 3rd International Workshop on Genetic and Evolving Fuzzy Systems (GEFS), WittenBommerholz (Germany), p.83-88, (2008)
Multi-class Imbalanced Data-Sets with Linguistic Fuzzy Rule Based Classification Systems Based on Pairwise Learning, Fernández, A., del Jesus M. J., and Herrera F. , 13th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU), June, Volume 6178, Dortmund (Germany), p.89-98, (2010)
Statistical Comparisons by Means of Non-Parametric Tests: A Case Study on Genetic Based Machine Learning, García, S., Fernández A., Benítez A.D., and Herrera F. , Proceedings of the II Congreso Español de Informática (CEDI 2007). V Taller Nacional de Minería de Datos y Aprendizaje (TAMIDA), September, Zaragoza (Spain), p.95-104, (2007)
Un primer estudio sobre el uso de los sistemas de clasificación basados en reglas difusas en problemas de clasificación con clases no balanceadas, Fernández, A., García S., Herrera F., and del Jesus M. J. , Proceedings of the XIII Congreso Español sobre Tecnologías y Lógica Fuzzy (ESTYLF), September, Ciudad Real (Spain), p.89-95, (2006)
Un Primer Estudio sobre la Utilización de Selección Evolutiva de Conjuntos de Entrenamiento en Problemas de Clasificación con Clases no Balanceadas y Árboles de Decisión, García, S., Fernández A., and Herrera F. , Proceedings of VI Congreso Español sobre Metaheurísticas, Algoritmos Evolutivos y Bioinspirados (MAEB), February, Málaga (Spain), p.183-190, (2009)
Journal Article
A Genetic Tuning to Improve the Performance of Fuzzy Rule-Based Classification Systems with Interval-Valued Fuzzy Sets: Degree of Ignorance and Lateral Position, Sanz, J., Fernández A., Bustince H., and Herrera F. , International Journal of Approximate Reasoning, Volume 52, Number 6, p.751-766, (2011)
A Pareto Based Ensemble with Feature and Instance Selection for Learning from Multi-Class Imbalanced Datasets, Fernández, A., Carmona C. J., del Jesus M. J., and Herrera F. , International Journal of Neural Systems, Volume 27, Issue 6, p.1-17, (2017) PDF icon 2017-Fernandez-IJNS.pdf (683.56 KB)
A Review on Ensembles for Class Imbalance Problem: Bagging, Boosting and Hybrid Based Approaches, Galar, M., Fernández A., Barrenechea E., Bustince H., and Herrera F. , IEEE Transactions on System, Man and Cybernetics - Part C: Applications and Reviews, Volume 42, Number 4, p.463-484, (2012)
A Study of the Behaviour of Linguistic Fuzzy Rule Based Classification Systems in the Framework of Imbalanced Data Sets, Fernández, A., García S., del Jesus M. J., and Herrera F. , Fuzzy Sets and Systems, Volume 159, Number 18, p.2378-2398, (2008)
A View on Fuzzy Systems for Big Data: Progress and Opportunities, Fernández, A., Carmona C. J., del Jesus M. J., and Herrera F. , International Journal of Computational Intelligence Systems, Volume 9, Number 1, p.69-80, (2016) PDF icon 2016-Fernandez-IJCIS.pdf (455.58 KB)
Addressing Data Complexity for Imbalanced Data Sets: Analysis of SMOTE-based Oversampling and Evolutionary Undersampling, Luengo, J., Fernández A., García S., and Herrera F. , Soft Computing, Volume 15, Number 10, p.1909-1936, (2011)
Advanced nonparametric tests for multiple comparisons in the design of experiments in computational intelligence and data mining: Experimental Analysis of Power, García, S., Fernández A., Luengo J., and Herrera F. , Information Sciences, Volume 180, p.2044–2064, (2010)
Analysis of preprocessing vs. cost-sensitive learning for imbalanced classification. Open problems on intrinsic data characteristics, López, V., Fernández A., Moreno-Torres J.G., and Herrera F. , Expert Systems with Applications, Volume 39, Number 7, p.6585-6608, (2012)
Automatic Laser Pointer Detection Algorithm for Environment Control Device Systems Based on Template Matching and Genetic Tuning of Fuzzy Rule-Based Systems, Chávez, F., Fernández A., Gacto M. J., and Alcalá R. , International Journal of Computational Intelligence Systems, Volume 5, Number 2, p.368-386, (2012)
Enhancing the Effectiveness and Interpretability of Decision Tree and Rule Induction Classifiers with Evolutionary Training Set Selection over Imbalanced Problems, García, S., Fernández A., and Herrera F. , Applied Soft Computing, Volume 9, p.1304-1314, (2009)
Evolutionary Fuzzy Sistems for Explainable Artificial Intelligence: Why, When, What for, and Where to ?, Fernández, A., del Jesus M. J., Cordón O., Marcelloni F., and Herrera F. , IEEE Computational Intelligence, Volume 1, Number 14, p.69-81, (2019) PDF icon 08610271.pdf (1.09 MB)
Feature Selection and Granularity Learning in Genetic Fuzzy Rule-Based Classication Systems for Highly Imbalanced Data-Sets, Villar, P., Fernández A., Carrasco R., and Herrera F. , International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, Volume 20, Number 3, p.369-397, (2012)
Genetics-Based Machine Learning for Rule Induction: State of the Art, Taxonomy and Comparative Study, Fernández, A., Luengo J., García S., Bernadó-Mansilla E., and Herrera F. , IEEE Transactions on Evolutionary Computation, Volume 14, Number 6, p.913-941, (2010)
Hierarchical fuzzy rule based classfication systems with genetic rule selection for imbalanced data-sets, Fernández, A., del Jesus M. J., and Herrera F. , International Journal of Approximate Reasoning, Volume 50, p.561-577, (2009)
IIVFDT: Ignorance Functions based Interval-Valued Fuzzy Decision Tree with Genetic Tuning. International Journal of Uncertainty, Sanz, J., Fernández A., and Bustince H. , International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, (2012)
Improving the Performance of Fuzzy Rule-Based Classification Systems with Interval-Valued Fuzzy Sets and Genetic Amplitude Tuning, Sanz, J., Fernández A., Bustince H., and Herrera F. , Information Sciences, Volume 180, Number 19, p.3674-3685, (2010)
KEEL 3.0: An Open Source Software for Multi-Stage Analysis in Data Mining., Triguero, I., Gonzalez S., Moyano J.M., García S., Alcalá-Fdez J., Luengo J., Fernández A., del Jesus M. J., Sánchez L., Herrera F., et al. , International Journal of Computational Intelligence Systems, Volume 10, Number 1, p.1238-1249, (2017)
KEEL Data-Mining Software Tool: Data Set Repository, Integration of Algorithms and Experimental Analysis Framework, Alcalá-Fdez, J., Fernández A., Luengo J., Derrac J., García S., Sánchez L., and Herrera F. , Journal of Multiple-Valued Logic and Soft Computing, Volume 17, Number 2-3, p.255-287, (2011)
On the 2-Tuples Based Genetic Tuning Performance for Fuzzy Rule Based Classification Systems in Imbalanced Data-Sets, Fernández, A., del Jesus M. J., and Herrera F. , Information Sciences, Volume 180, Number 8, p.1268-1291, (2010)
On the influence of an adaptive inference system in fuzzy rule-based classification sytems for imbalanced data-sets, Fernández, A., Herrera F., and del Jesus M. J. , Expert Systems with Applications, Volume 36, Number 6, p.9805-9812, (2009)
Propuesta de una asignatura de Diseño de Servidores para la especialidad de Tecnologías de Información, Rivera-Rivas, A.J., Espinilla Macarena, Fernández A., López José Santamarí, and Charte Francisco , Enseñanza y aprendizaje de ingeniería de computadores. Revista de experiencias docentes en ingeniería de computadores, Volume 4, p.15–24, (2014) PDF icon 2014-EAIC14-AsignaturaDisenoServ.pdf (864.57 KB)
Solving Multi-Class Problems with Linguistic Fuzzy Rule Based Classification Systems Based on Pairwise Learning and Preference Relations, Fernández, A., Calderón M., Barrenechea E., Bustince H., and Herrera F. , Fuzzy Sets and Systems, Volume 161, Number 23, p.3064-3080, (2010)