Francisco Herrera Triguero

First name
Francisco
Last name
Herrera Triguero

2018

Carmona, C. J. ., del Jesus Díaz, M. J. ., & Herrera Triguero, F. . (2018). A Unifying Analysis for the Supervised Descriptive Rule Discovery via the Weighted Relative Accuracy. Knowledge-Based Systems, 139, 89-100. https://doi.org/10.1016/j.knosys.2017.10.015
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Carmona, C. J. ., del Jesus Díaz, M. J. ., & Herrera Triguero, F. . (2018). Atipicidad: Medida de calidad clave dentro del descubrimiento de reglas descriptivas supervisadas. 827-828.
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Charte Ojeda, F. ., Rivera Rivas, A. J. ., Charte, D. ", del Jesus Díaz, M. J. ., & Herrera Triguero, F. . (2018). Tips, guidelines and tools for managing multi-label datasets: The mldr.datasets R package and the Cometa data repository. Neurocomputing, 289, 68-85. https://doi.org/10.1016/j.neucom.2018.02.011
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Fernández Hilario, A. L. . ., Carmona, C. J. ., del Jesus Díaz, M. J. ., & Herrera Triguero, F. . (2018). A Pareto Based Ensemble with Feature and Instance Selection for Learning from Multi-Class Imbalanced Datasets. Proc. Of the XVIII Conferencia De La Asociación Española Para La Inteligencia Artificial (XVIII CAEPIA), 1316-1317.
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Charte, D. ", Charte Ojeda, F. ., García López, S. ., del Jesus Díaz, M. J. ., & Herrera Triguero, F. . (2018). A practical tutorial on autoencoders for nonlinear feature fusion: Taxonomy, models, software and guidelines. 949-950. Granada (Spain). (Original work published)
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2017

Prati, R. C., Charte Ojeda, F. ., & Herrera Triguero, F. . (2017). A first approach towards a fuzzy decision tree for multilabel classification. 1-6. Naples (Italy). https://doi.org/10.1109/FUZZ-IEEE.2017.8015521 (Original work published)
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Fernández Hilario, A. L. . ., Carmona, C. J. ., del Jesus Díaz, M. J. ., & Herrera Triguero, F. . (2017). A Pareto Based Ensemble with Feature and Instance Selection for Learning from Multi-Class Imbalanced Datasets. International Journal of Neural Systems, 27, 1-17. https://doi.org/10.1142/S0129065717500289
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Triguero, I. ., Gonzalez, S. ., Moyano, J. ., García López, S. ., Alcala-Fdez, J. ., Luengo, J. ., … PRESS., A. . (2017). KEEL 3.0: An Open Source Software for Multi-Stage Analysis in Data Mining. International Journal of Computational Intelligence Systems, 10, 1238-1249.
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2016

Charte Ojeda, F. ., Rivera Rivas, A. J. ., del Jesus Díaz, M. J. ., & Herrera Triguero, F. . (2016). On the Impact of Dataset Complexity and Sampling Strategy in Multilabel Classifiers Performance. 500-511. Seville (Spain). https://doi.org/10.1007/978-3-319-32034-2_42 (Original work published)
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Charte Ojeda, F. ., Charte, D. ", Rivera Rivas, A. J. ., del Jesus Díaz, M. J. ., & Herrera Triguero, F. . (2016). R Ultimate Multilabel Dataset Repository. 487-499. Seville (Spain). https://doi.org/10.1007/978-3-319-32034-2_41 (Original work published)
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