Publicaciones en colaboración con investigadores/as de Universidad de Granada (38)

2016

  1. A first study on the use of boosting for class noise reparation

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

  2. Evaluating the classifier behavior with noisy data considering performance and robustness: The Equalized Loss of Accuracy measure

    Neurocomputing, Vol. 176, pp. 26-35

  3. From Big Data to Smart Data with the K-Nearest Neighbours Algorithm

    Proceedings - 2016 IEEE International Conference on Internet of Things; IEEE Green Computing and Communications; IEEE Cyber, Physical, and Social Computing; IEEE Smart Data, iThings-GreenCom-CPSCom-Smart Data 2016

  4. INFFC: An iterative class noise filter based on the fusion of classifiers with noise sensitivity control

    Information Fusion, Vol. 27, pp. 19-32

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

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

  6. Tutorial on practical tips of the most influential data preprocessing algorithms in data mining

    Knowledge-Based Systems, Vol. 98, pp. 1-29

2015

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

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

  2. An automatic extraction method of the domains of competence for learning classifiers using data complexity measures

    Knowledge and Information Systems, Vol. 42, Núm. 1, pp. 147-180

  3. Data Preprocessing in Data Mining

    Intelligent Systems Reference Library, Vol. 72

  4. Data preparation basic models

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

  5. Data reduction

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

  6. Data sets and proper statistical analysis of data mining techniques

    Intelligent Systems Reference Library, Vol. 72, pp. 19-38

  7. Dealing with missing values

    Intelligent Systems Reference Library, Vol. 72, pp. 59-105

  8. Dealing with noisy data

    Intelligent Systems Reference Library, Vol. 72, pp. 107-145

  9. Discretization

    Intelligent Systems Reference Library, Vol. 72, pp. 245-283

  10. Feature selection

    Intelligent Systems Reference Library, Vol. 72, pp. 163-193

  11. Instance selection

    Intelligent Systems Reference Library, Vol. 72, pp. 195-243

  12. Introduction

    Intelligent Systems Reference Library, Vol. 72, pp. 1-17

  13. SMOTE-IPF: Addressing the noisy and borderline examples problem in imbalanced classification by a re-sampling method with filtering

    Information Sciences, Vol. 291, Núm. C, pp. 184-203

  14. Using the One-vs-One decomposition to improve the performance of class noise filters via an aggregation strategy in multi-class classification problems

    Knowledge-Based Systems, Vol. 90, pp. 153-164