Publicaciones en las que colabora con ALBERTO LUIS FERNÁNDEZ HILARIO (105)

2022

  1. FW-SMOTE: A feature-weighted oversampling approach for imbalanced classification

    Pattern Recognition, Vol. 124

2021

  1. Learning interpretable multi-class models by means of hierarchical decomposition: Threshold Control for Nested Dichotomies

    Neurocomputing, Vol. 463, pp. 514-524

  2. Revisiting data complexity metrics based on morphology for overlap and imbalance: snapshot, new overlap number of balls metrics and singular problems prospect

    Knowledge and Information Systems, Vol. 63, Núm. 7, pp. 1961-1989

  3. SOUL: Scala Oversampling and Undersampling Library for imbalance classification

    SoftwareX, Vol. 15

2020

  1. HFER: Promoting explainability in fuzzy systems via hierarchical fuzzy exception rules

    IEEE International Conference on Fuzzy Systems

2019

  1. A Metahierarchical Rule Decision System to Design Robust Fuzzy Classifiers Based on Data Complexity

    IEEE Transactions on Fuzzy Systems, Vol. 27, Núm. 4, pp. 701-715

  2. A multi-objective evolutionary fuzzy system to obtain a broad and accurate set of solutions in intrusion detection systems

    Soft Computing, Vol. 23, Núm. 4, pp. 1321-1336

  3. An analysis of local and global solutions to address big data imbalanced classification: A case study with smote preprocessing

    Communications in Computer and Information Science

  4. 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

  5. Evolutionary fuzzy systems: A case study for intrusion detection systems

    Studies in Computational Intelligence (Springer Verlag), pp. 169-190

  6. Guest Editorial: Computational Intelligence for Big Data Analytics

    Cognitive Computation

2018

  1. Big Data: Tutorial and guidelines on information and process fusion for analytics algorithms with MapReduce

    Information Fusion, Vol. 42, pp. 51-61

  2. Dynamic affinity-based classification of multi-class imbalanced data with one-versus-one decomposition: a fuzzy rough set approach

    Knowledge and Information Systems, Vol. 56, Núm. 1, pp. 55-84

  3. Imbalance: Oversampling algorithms for imbalanced classification in R

    Knowledge-Based Systems, Vol. 161, pp. 329-341

  4. NMC, Nearest Matrix Classification: a new combination model for pruning one-vs-one ensembles by transforming the aggregation problem

    XVIII Conferencia de la Asociación Española para la Inteligencia Artificial (CAEPIA 2018): avances en Inteligencia Artificial. 23-26 de octubre de 2018 Granada, España

  5. 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

  6. SMOTE for Learning from Imbalanced Data: Progress and Challenges, Marking the 15-year Anniversary

    Journal of Artificial Intelligence Research, Vol. 61, pp. 863-905

  7. SMOTE-BD: an Exact and Scalable Oversampling Method for Imbalanced Classification in Big Data

    Journal of Computer Science and Technology, Vol. 18, Núm. 3

  8. Surveying alignment-free features for Ortholog detection in related yeast proteomes by using supervised big data classifiers

    BMC Bioinformatics, Vol. 19, Núm. 1

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