María Del Mar Martínez Ballesteros-rekin lankidetzan egindako argitalpenak (27)

2023

  1. A Feature Selection and Association Rule Approach to Identify Genes Associated with Metastasis and Low Survival in Sarcoma

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

2018

  1. An approach to validity indices for clustering techniques in Big Data

    Progress in Artificial Intelligence, Vol. 7, Núm. 2, pp. 81-94

  2. Aproximación al índice externo de validación de clustering basado en chi cuadrado

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

  3. MRQAR: A generic MapReduce framework to discover quantitative association rules in big data problems

    Knowledge-Based Systems, Vol. 153, pp. 176-192

2017

  1. A study of the suitability of autoencoders for preprocessing data in breast cancer experimentation

    Journal of Biomedical Informatics, Vol. 72, pp. 33-44

  2. Applications of Computational Intelligence in Time Series

    Computational Intelligence and Neuroscience

  3. Machine learning techniques to discover genes with potential prognosis role in Alzheimer's disease using different biological sources

    Information Fusion, Vol. 36, pp. 114-129

  4. Predicción de módulos defectuosos como un problema de optimización multiobjetivo

    Actas de las 22nd Jornadas de Ingenier�a del Software y Bases de Datos, JISBD 2017

  5. Predicción de módulos defectuosos como un problema de optimización multiobjetivo

    Actas de las 22nd Jornadas de Ingenier�a del Software y Bases de Datos, JISBD 2017

2016

  1. An approach to silhouette and dunn clustering indices applied to big data in spark

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

  2. Improving a multi-objective evolutionary algorithm to discover quantitative association rules

    Knowledge and Information Systems, Vol. 49, Núm. 2, pp. 481-509

  3. Obtaining optimal quality measures for quantitative association rules

    Neurocomputing, Vol. 176, pp. 36-47

2013

  1. A sensitivity analysis for quality measures of quantitative association rules

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