ALBERTO LUIS
FERNÁNDEZ HILARIO
CATEDRÁTICO DE UNIVERSIDAD
Universidad de Jaén
Jaén, EspañaPublicaciones en colaboración con investigadores/as de Universidad de Jaén (77)
2019
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Evolutionary fuzzy systems for explainable artificial intelligence: Why, when, what for, and where to?
IEEE Computational Intelligence Magazine, Vol. 14, Núm. 1, pp. 69-81
2018
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Pareto based ensemble with feature and instance selection for learning from multi-class imbalanced datasets
XVIII Conferencia de la Asociación Española para la Inteligencia Artificial (CAEPIA 2018): avances en Inteligencia Artificial. 23-26 de octubre de 2018 Granada, España
2017
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A pareto-based ensemble with feature and instance selection for learning from multi-class imbalanced datasets
International Journal of Neural Systems, Vol. 27, Núm. 6
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KEEL 3.0: An Open Source Software for Multi-Stage Analysis in Data Mining
International Journal of Computational Intelligence Systems, Vol. 10, Núm. 1, pp. 1238-1249
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NMC: nearest matrix classification – A new combination model for pruning One-vs-One ensembles by transforming the aggregation problem
Information Fusion, Vol. 36, pp. 26-51
2016
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A View on Fuzzy Systems for Big Data: Progress and Opportunities
International Journal of Computational Intelligence Systems, Vol. 9, pp. 69-80
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A first approach in evolutionary fuzzy systems based on the lateral tuning of the linguistic labels for big data classification
2016 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2016
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Enhancing evolutionary fuzzy systems for multi-class problems: Distance-based relative competence weighting with truncated confidences (DRCW-TC)
International Journal of Approximate Reasoning, Vol. 73, pp. 108-122
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Evolutionary fuzzy systems: A case study in imbalanced classification
Studies in Fuzziness and Soft Computing (Springer Verlag), pp. 169-200
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New ordering-based pruning metrics for ensembles of classifiers in imbalanced datasets
Advances in Intelligent Systems and Computing
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On the combination of pairwise and granularity learning for improving fuzzy rule-based classification systems: GL-FARCHD-OVO
Advances in Intelligent Systems and Computing
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Ordering-based pruning for improving the performance of ensembles of classifiers in the framework of imbalanced datasets
Information Sciences, Vol. 354, pp. 178-196
2015
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A proposal for evolutionary fuzzy systems using feature weighting: Dealing with overlapping in imbalanced datasets
Knowledge-Based Systems, Vol. 73, pp. 1-17
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Addressing overlapping in classification with imbalanced datasets: A first multi-objective approach for feature and instance selection
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
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DRCW-OVO: Distance-based relative competence weighting combination for One-vs-One strategy in multi-class problems
Pattern Recognition, Vol. 48, Núm. 1, pp. 28-42
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Enhancing Multiclass Classification in FARC-HD Fuzzy Classifier: On the Synergy Between n-Dimensional Overlap Functions and Decomposition Strategies
IEEE Transactions on Fuzzy Systems, Vol. 23, Núm. 5, pp. 1562-1580
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Improving Pairwise Learning Classification in Fuzzy Rule Based Classification Systems Using Dynamic Classifier Selection
Proceedings of the 2015 conference of the international fuzzy systems association and the european society for fuzzy logic and technology
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Improving the OVO performance in Fuzzy Rule-Based Classification Systems by the genetic learning of the granularity level
IEEE International Conference on Fuzzy Systems
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Improving the OVO performance in fuzzy rule-based classification systems by the genetic learning of the granularity level
2015 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ-IEEE 2015)
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On the combination of genetic fuzzy systems and pairwise learning for improving detection rates on Intrusion Detection Systems
Expert Systems with Applications, Vol. 42, Núm. 1, pp. 193-202