Publicaciones en las que colabora con Laura Morán Fernández (20)

2022

  1. Feature Selection: From the Past to the Future

    Learning and Analytics in Intelligent Systems (Springer Nature), pp. 11-34

  2. How important is data quality? Best classifiers vs best features

    Neurocomputing, Vol. 470, pp. 365-375

  3. Low-precision feature selection on microarray data: an information theoretic approach

    Medical and Biological Engineering and Computing, Vol. 60, Núm. 5, pp. 1333-1345

2020

  1. Do we need hundreds of classifiers or a good feature selection?

    ESANN 2020 - Proceedings, 28th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning

  2. Feature selection with limited bit depth mutual information for portable embedded systems

    Knowledge-Based Systems, Vol. 197

  3. When Size Matters: Markov Blanket with Limited Bit Depth Conditional Mutual Information

    Communications in Computer and Information Science

2019

  1. A Review of Microarray Datasets: Where to Find Them and Specific Characteristics

    Methods in Molecular Biology (Humana Press Inc.), pp. 65-85

  2. Distributed classification based on distances between probability distributions in feature space

    Information Sciences, Vol. 496, pp. 431-450

  3. Feature Selection Applied to Microarray Data

    Methods in Molecular Biology (Humana Press Inc.), pp. 123-152

2018

  1. Análisis de algoritmos de cuantificación basados en ajuste de distribuciones

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

  2. Preprocessing in High Dimensional Datasets

    Intelligent Systems Reference Library (Springer Science and Business Media Deutschland GmbH), pp. 247-271

2017

  1. A distributed approach for classification using distance metrics

    ESANN 2017 - Proceedings, 25th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning

  2. Can classification performance be predicted by complexity measures? A study using microarray data

    Knowledge and Information Systems, Vol. 51, Núm. 3, pp. 1067-1090

  3. Centralized vs. distributed feature selection methods based on data complexity measures

    Knowledge-Based Systems, Vol. 117, pp. 27-45

  4. On the use of different base classifiers in multiclass problems

    Progress in Artificial Intelligence, Vol. 6, Núm. 4, pp. 315-323

2016

  1. Data complexity measures for analyzing the effect of SMOTE over microarrays

    ESANN 2016 - 24th European Symposium on Artificial Neural Networks

  2. Selection of the best base classifier in one-versus-one using data complexity measures

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

2015

  1. A time efficient approach for distributed feature selection partitioning by features

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

  2. An insight on complexity measures and classification in microarray data

    2015 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN)

  3. An insight on complexity measures and classification in microarray data

    Proceedings of the International Joint Conference on Neural Networks