Juan Antonio Romero del Castillo

According to our database, Juan Antonio Romero del Castillo authored at least 9 papers between 2010 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2023

PARIS: Partial instance and training set selection. A new scalable approach to multi-label classification.

Nicolás García-Pedrajas, José Manuel Cuevas-Muñoz, Juan Antonio Romero del Castillo, Aida de Haro-García

Inf. Fusion, July, 2023

2022

Local-based k values for multi-label k-nearest neighbors rule.

Juan Antonio Romero del Castillo, Manuel Mendoza-Hurtado, Domingo Ortiz-Boyer, Nicolás García-Pedrajas

Eng. Appl. Artif. Intell., 2022

2021

SI(FS)2: Fast simultaneous instance and feature selection for datasets with many features.

Nicolás García-Pedrajas, Juan Antonio Romero del Castillo, Gonzalo Cerruela García

Pattern Recognit., 2021

Instance selection for multi-label learning based on a scalable evolutionary algorithm.

Juan Antonio Romero del Castillo, Domingo Ortiz-Boyer, Nicolás García-Pedrajas

Proceedings of the 2021 International Conference on Data Mining, 2021

2018

A general framework for boosting feature subset selection algorithms.

Javier Pérez-Rodríguez, Aida de Haro-García, Juan Antonio Romero del Castillo, Nicolás García-Pedrajas

Inf. Fusion, 2018

2017

A Proposal for Local k Values for k-Nearest Neighbor Rule.

Nicolás García-Pedrajas, Juan Antonio Romero del Castillo, Gonzalo Cerruela García

IEEE Trans. Neural Networks Learn. Syst., 2017

2012

Large scale instance selection by means of federal instance selection.

Aida de Haro-García, Nicolás García-Pedrajas, Juan Antonio Romero del Castillo

Data Knowl. Eng., 2012

2010

A cooperative coevolutionary algorithm for instance selection for instance-based learning.

Nicolás García-Pedrajas, Juan Antonio Romero del Castillo, Domingo Ortiz-Boyer

Mach. Learn., 2010

Large Scale Instance Selection by Means of a Parallel Algorithm.

Aida de Haro-García, Juan Antonio Romero del Castillo, Nicolás García-Pedrajas

Proceedings of the Intelligent Data Engineering and Automated Learning, 2010