Publicaciones (63) Publicaciones de ALBERTO FERNÁNDEZ HILARIO

2019

  1. 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

  1. 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

  1. 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

  2. A review of distributed data models for learning

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

  3. An insight into imbalanced Big Data classification: outcomes and challenges

    COMPLEX & INTELLIGENT SYSTEMS, Vol. 3, Núm. 2, pp. 105-120

  4. Chi-Spark-RS: An Spark-built evolutionary fuzzy rule selection algorithm in imbalanced classification for big data problems

    IEEE International Conference on Fuzzy Systems

  5. Chi-Spark-RS: an Spark-built Evolutionary Fuzzy Rule Selection Algorithm in Imbalanced Classification for Big Data Problems

    2017 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ-IEEE)

  6. Fuzzy rule based classification systems for big data with MapReduce: granularity analysis

    Advances in Data Analysis and Classification, Vol. 11, Núm. 4, pp. 711-730

  7. 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

  8. 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

  9. Why Linguistic Fuzzy Rule Based Classification Systems perform well in Big Data Applications?

    International Journal of Computational Intelligence Systems, Vol. 10, Núm. 1, pp. 1211-1225