ALBERTO
FERNÁNDEZ HILARIO
Researcher in the period 2013-2016
Mikel
Galar Idoate
Publications by the researcher in collaboration with Mikel Galar Idoate (13)
2017
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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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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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New ordering-based pruning metrics for ensembles of classifiers in imbalanced datasets
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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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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On the impact of Distance-based Relative Competence Weighting approach in One-vs-One classification for Evolutionary Fuzzy Systems: DRCW-FH-GBML algorithm
IEEE International Conference on Fuzzy Systems
2014
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Empowering difficult classes with a similarity-based aggregation in multi-class classification problems
Information Sciences, Vol. 264, pp. 135-157
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Enhancing difficult classes in one-vs-one classifier fusion strategy using restricted equivalence functions
FUSION 2014 - 17th International Conference on Information Fusion
2013
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Analysing the classification of imbalanced data-sets with multiple classes: Binarization techniques and ad-hoc approaches
Knowledge-Based Systems, Vol. 42, pp. 97-110
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Dynamic classifier selection for One-vs-One strategy: Avoiding non-competent classifiers
Pattern Recognition, Vol. 46, Núm. 12, pp. 3412-3424
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EUSBoost: Enhancing ensembles for highly imbalanced data-sets by evolutionary undersampling
Pattern Recognition, Vol. 46, Núm. 12, pp. 3460-3471