Publicaciones en colaboración con investigadores/as de Universidad de Burgos (33)

2024

  1. A comparative analysis of machine learning methods for display characterization

    Displays, Vol. 85

2018

  1. A unifying analysis for the supervised descriptive rule discovery via the weighted relative accuracy

    Knowledge-Based Systems, Vol. 139, pp. 89-100

  2. An overview of emerging pattern mining in supervised descriptive rule discovery: taxonomy, empirical study, trends, and prospects

    Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, Vol. 8, Núm. 1

  3. Improvement of subgroup descriptions in noisy data by detecting exceptions

    Progress in Artificial Intelligence, Vol. 7, Núm. 1, pp. 55-64

2017

  1. A first approach to handle fuzzy emerging patterns mining on big data problems: The EvAEFP-spark algorithm

    IEEE International Conference on Fuzzy Systems

  2. 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

  3. Analysing Concentrating Photovoltaics Technology Through the Use of Emerging Pattern Mining

    International Joint Conference SOCO’16-CISIS’16-ICEUTE’16: San Sebastián, Spain, October 19th-21st, 2016 Proceedings

  4. Analysing concentrating photovoltaics technology through the use of emerging pattern mining

    Advances in Intelligent Systems and Computing

  5. MEFASD-BD: Multi-objective evolutionary fuzzy algorithm for subgroup discovery in big data environments - A MapReduce solution

    Knowledge-Based Systems, Vol. 117, pp. 70-78

2016

  1. A View on Fuzzy Systems for Big Data: Progress and Opportunities

    International Journal of Computational Intelligence Systems, Vol. 9, pp. 69-80

  2. Estimating the maximum power delivered by concentrating photovoltaics technology through atmospheric conditions using a differential evolution approach

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

  3. Subgroup discovery with evolutionary fuzzy systems in r: The SDEFSR package

    R Journal, Vol. 8, Núm. 2, pp. 307-323

  4. The influence of noise on the evolutionary fuzzy systems for subgroup discovery

    Soft Computing, Vol. 20, Núm. 11, pp. 4313-4330

2015

  1. A data mining software package including data preparation and reduction: Keel

    Intelligent Systems Reference Library, Vol. 72, pp. 285-313

  2. A differential evolution proposal for estimating the maximum power delivered by CPV modules under real outdoor conditions

    Expert Systems with Applications, Vol. 42, Núm. 13, pp. 5452-5462

  3. A first approach in the class noise filtering approaches for fuzzy subgroup discovery

    Advances in Intelligent Systems and Computing

  4. A fuzzy genetic programming-based algorithm for subgroup discovery and the application to one problem of pathogenesis of acute sore throat conditions in humans

    Information Sciences, Vol. 298, pp. 180-197

  5. Data Preprocessing in Data Mining

    Intelligent Systems Reference Library, Vol. 72

  6. Data preparation basic models

    Intelligent Systems Reference Library, Vol. 72, pp. 39-57

  7. Data reduction

    Intelligent Systems Reference Library, Vol. 72, pp. 147-162