Publicaciones en las que colabora con Antonio Jesús Rivera Rivas (18)

2019

  1. Dealing with difficult minority labels in imbalanced mutilabel data sets

    Neurocomputing, Vol. 326-327, pp. 39-53

  2. REMEDIAL-HwR: Tackling multilabel imbalance through label decoupling and data resampling hybridization

    Neurocomputing, Vol. 326-327, pp. 110-122

2018

  1. Tips, guidelines and tools for managing multi-label datasets: The mldr.datasets R package and the Cometa data repository

    Neurocomputing, Vol. 289, pp. 68-85

2016

  1. Multilabel classification: Problem analysis, metrics and techniques

    Springer International Publishing, pp. 1-194

  2. On the impact of dataset complexity and sampling strategy in multilabel classifiers performance

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

  3. R ultimate multilabel dataset repository

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

2015

  1. Addressing imbalance in multilabel classification: Measures and random resampling algorithms

    Neurocomputing, Vol. 163, pp. 3-16

  2. MLSMOTE: Approaching imbalanced multilabel learning through synthetic instance generation

    Knowledge-Based Systems, Vol. 89, pp. 385-397

  3. QUINTA: A Question Tagging Assistant to Improve the Answering Ratio in Electronic Forums

    IEEE EUROCON 2015 - INTERNATIONAL CONFERENCE ON COMPUTER AS A TOOL (EUROCON)

  4. QUINTA: A question tagging assistant to improve the answering ratio in electronic forums

    Proceedings - EUROCON 2015

  5. Resampling multilabel datasets by decoupling highly imbalanced labels

    Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)

2014

  1. Concurrence among imbalanced labels and its influence on multilabel resampling algorithms

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

  2. LI-MLC: A label inference methodology for addressing high dimensionality in the label space for multilabel classification

    IEEE Transactions on Neural Networks and Learning Systems, Vol. 25, Núm. 10, pp. 1842-1854

  3. MLeNN: A first approach to heuristic multilabel undersampling

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

2013

  1. A first approach to deal with imbalance in multi-label datasets

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

2012

  1. Improving multi-label classifiers via label reduction with association rules

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

2010

  1. GP-COACH: Genetic Programming-based learning of COmpact and ACcurate fuzzy rule-based classification systems for High-dimensional problems

    Information Sciences, Vol. 180, Núm. 8, pp. 1183-1200

2009

  1. A preliminar analysis of CO2RBFN in imbalanced problems

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