Research publications
Journal papers
Mario Frias*, Jose M. Moyano*, Antonio Rivero-Juarez, Jose M. Luna, Ángela Camacho, Habib M. Fardoun, Isabel Machuca, Mohamed Al-Twijri, Antonio Rivero, Sebastian Ventura. (2021). Data mining approach improves classification accuracy of HCV infection outcome. Journal of Medical Internet Research, In press. DOI: 10.2196/18766. Bibtex.
[*Both authors contributed equally.]
Jose M. Moyano, Oscar Reyes, Habib M. Fardoun, Sebastian Ventura. (2021). Performing multi-target regression via gene expression programming-based ensemble models. Neurocomputing, 432: 275-287. DOI: 10.1016/j.neucom.2020.12.060. Bibtex.
Jose M. Moyano, Eva L. Gibaja, Krzysztof J. Cios, and Sebastián Ventura. (2020). Combining multi-label classifiers based on projections of the output space using Evolutionary algorithms. Knowledge-Based Systems, 196: 105770. DOI: 10.1016/j.knosys.2020.105770. Bibtex.
Jose M. Moyano, Eva L. Gibaja, Krzysztof J. Cios, and Sebastián Ventura. (2019). An Evolutionary approach to build ensembles of multi-label classifiers. Information Fusion, 50: 168-180. DOI: 10.1016/j.inffus.2018.11.013. Bibtex.
Jose M. Moyano, Eva L. Gibaja, Krzysztof J. Cios, and Sebastián Ventura. (2018). Review of ensembles of multi-label classifiers: Models, experimental study and prospects. Information Fusion, 44: 33-45. DOI: 10.1016/j.inffus.2017.12.001. Bibtex.
Isaac Triguero, Sergio González, Jose M. Moyano, Salvador García, Jesús Alcalá-Fdez, Julián Luengo, Alberto Fernández, Maria José del Jesus, Luciano Sánchez, and Francisco Herrera. (2017). KEEL 3.0: An open source software for multi-stage analysis in data mining. International Journal of Computational Intelligence Systems, 10(1): 1238-1249. DOI: 10.2991/ijcis.10.1.82. Bibtex.
Jose M. Moyano, Eva L. Gibaja, and Sebastián Ventura. (2017). MLDA: A tool for analyzing multi-label datasets. Knowledge-Based Systems, 121: 1-3. DOI: 10.1016/j.knosys.2017.01.018. Bibtex.
Eva L. Gibaja, Jose M. Moyano, and Sebastián Ventura. (2016). An ensemble-based approach for multi-view multi-label classification. Progress in Artificial Intelligence, 5(4): 251-259. DOI: 10.1007/s13748-016-0098-9. Bibtex.