Charte Ojeda, F., Rivera Rivas, A. J., del Jesus Díaz, M. J., & Herrera Triguero, F. (2015). Addressing imbalance in multilabel classification: Measures and random resampling algorithms. Neurocomputing, 163, 3-16. https://doi.org/10.1016/j.neucom.2014.08.091
Francisco Charte Ojeda
First name
Francisco
Last name
Charte Ojeda
2015
Rivera Rivas, A. J., Pérez Godoy, M. D., Charte Ojeda, F., Pulgar Rubio, F. J., & del Jesus Díaz, M. J. (2015). An ensemble strategy for forecasting the extra-virgin olive oil price in Spain. 506-516. Granada (Spain). (Original work published)
Pérez Godoy, M. D., Rivera Rivas, A. J., Charte Ojeda, F., & del Jesus Díaz, M. J. (2015). CO2RBFN-CS: First Approach Introducing Cost-Sensitivity in the Cooperative-Competitive RBFN Design. 361-373. Palma de Mallorca (Spain). https://doi.org/10.1007/978-3-319-19258-1_31 (Original work published)
Charte Ojeda, F. (2015). Nuevos métodos de computación flexible para clasificación multietiqueta (Universidad de Jaén; p. 275). Universidad de Jaén, Jaén. Recuperado de https://fcharte.com/assets/pdfs/PhdThesis-CharteFco.pdf
Bibliography media
Notes
Tesis doctoral en el Programa Oficial de Doctorado en Tecnologías de la Información y la Comunicación
Charte, D. ", & Charte Ojeda, F. (2015). mldr: Paquete R para Exploración de Datos Multietiqueta. 695-704. Albacete (Spain). (Original work published)
Charte Ojeda, F., Rivera Rivas, A. J., del Jesus Díaz, M. J., & Herrera Triguero, F. (2015). MLSMOTE: Approaching imbalanced multilabel learning through synthetic instance generation. Knowledge-Based Systems, 89, 385-397. https://doi.org/10.1016/j.knosys.2015.07.019
Charte Ojeda, F., Rivera Rivas, A. J., del Jesus Díaz, M. J., & Herrera Triguero, F. (2015). QUINTA: A question tagging assistant to improve the answering ratio in electronic forums. 1-6. Salamanca (Spain). https://doi.org/10.1109/EUROCON.2015.7313677 (Original work published)
Charte Ojeda, F., Rivera Rivas, A. J., del Jesus Díaz, M. J., & Herrera Triguero, F. (2015). Resampling Multilabel Datasets by Decoupling Highly Imbalanced Labels. 489-501. Bilbao (Spain). https://doi.org/10.1007/978-3-319-19644-2_41 (Original work published)
2014
Charte Ojeda, F., Rivera Rivas, A. J., del Jesus Díaz, M. J., & Herrera Triguero, F. (2014). Concurrence among Imbalanced Labels and Its Influence on Multilabel Resampling Algorithms. 110-121. Salamanca (Spain). https://doi.org/10.1007/978-3-319-07617-1_10 (Original work published)
Charte Ojeda, F., Rivera Rivas, A. J., del Jesus Díaz, M. J., & Herrera Triguero, F. (2014). LI-MLC: A Label Inference Methodology for Addressing High Dimensionality in the Label Space for Multilabel Classification. IEEE Transactions on Neural Networks and Learning Systems, 25, 1842-1854. https://doi.org/10.1109/TNNLS.2013.2296501