Jose M. Moyano

According to our database, Jose M. Moyano authored at least 18 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

A Tutorial on Federated Learning from Theory to Practice: Foundations, Software Frameworks, Exemplary Use Cases, and Selected Trends.

María Victoria Luzón, Nuria Rodríguez Barroso, Alberto Argente-Garrido, Daniel Jiménez-López, Jose M. Moyano, Javier Del Ser, Weiping Ding, Francisco Herrera

IEEE CAA J. Autom. Sinica, April, 2024

2022

Auto-adaptive Grammar-Guided Genetic Programming algorithm to build Ensembles of Multi-Label Classifiers.

Jose M. Moyano, Sebastián Ventura

Inf. Fusion, 2022

Reducing the Label Space a Predefined Ratio for a More Efficient Multilabel Classification.

Jose M. Moyano, José María Luna, Sebastián Ventura

IEEE Access, 2022

Improving the Performance of Multi-Label Classifiers via Label Space Reduction.

Jose M. Moyano, José María Luna, Sebastián Ventura

Proceedings of the IEEE International Conference on Omni-layer Intelligent Systems, 2022

2021

Performing multi-target regression via gene expression programming-based ensemble models.

Jose M. Moyano, Oscar Gabriel Reyes Pupo, Habib M. Fardoun, Sebastián Ventura

Neurocomputing, 2021

2020

Combining multi-label classifiers based on projections of the output space using Evolutionary algorithms.

Jose M. Moyano, Eva Gibaja, Krzysztof J. Cios, Sebastián Ventura

Knowl. Based Syst., 2020

Generating Ensembles of Multi-Label Classifiers Using Cooperative Coevolutionary Algorithms.

Jose M. Moyano, Eva L. Gibaja, Krzysztof J. Cios, Sebastián Ventura

Proceedings of the ECAI 2020 - 24th European Conference on Artificial Intelligence, 29 August-8 September 2020, Santiago de Compostela, Spain, August 29 - September 8, 2020, 2020

Tree-Shaped Ensemble of Multi-Label Classifiers using Grammar-Guided Genetic Programming.

Jose M. Moyano, Eva Lucrecia Gibaja Galindo, Krzysztof J. Cios, Sebastián Ventura

Proceedings of the IEEE Congress on Evolutionary Computation, 2020

2019

An evolutionary approach to build ensembles of multi-label classifiers.

Jose M. Moyano, Eva Lucrecia Gibaja Galindo, Krzysztof J. Cios, Sebastián Ventura

Inf. Fusion, 2019

Speeding Up Classifier Chains in Multi-label Classification.

Jose M. Moyano, Eva Gibaja, Sebastián Ventura, Alberto Cano

Proceedings of the 4th International Conference on Internet of Things, 2019

2018

Review of ensembles of multi-label classifiers: Models, experimental study and prospects.

Jose M. Moyano, Eva Lucrecia Gibaja Galindo, Krzysztof J. Cios, Sebastián Ventura

Inf. Fusion, 2018

A gene expression programming method for multi-target regression.

Oscar Gabriel Reyes Pupo, Jose María Moyano Murillo, José María Luna, Sebastián Ventura

Proceedings of the International Conference on Learning and Optimization Algorithms: Theory and Applications, 2018

2017

MLDA: A tool for analyzing multi-label datasets.

Jose M. Moyano, Eva Lucrecia Gibaja Galindo, Sebastián Ventura

Knowl. Based Syst., 2017

KEEL 3.0: An Open Source Software for Multi-Stage Analysis in Data Mining.

Isaac Triguero, Sergio González, Jose M. Moyano, Salvador García, Jesús Alcalá-Fdez, Julián Luengo, Alberto Fernández, María José del Jesus, Luciano Sánchez, Francisco Herrera

Int. J. Comput. Intell. Syst., 2017

Mining association rules in R using the package RKEEL.

Oliver Sanchez, Jose M. Moyano, Luciano Sánchez, Jesús Alcalá-Fdez

Proceedings of the 2017 IEEE International Conference on Fuzzy Systems, 2017

An evolutionary algorithm for optimizing the target ordering in Ensemble of Regressor Chains.

Jose M. Moyano, Eva Lucrecia Gibaja Galindo, Sebastián Ventura

Proceedings of the 2017 IEEE Congress on Evolutionary Computation, 2017

2016

An ensemble-based approach for multi-view multi-label classification.

Eva Gibaja, Jose M. Moyano, Sebastián Ventura

Prog. Artif. Intell., 2016

RKEEL: Using KEEL in R code.

Jose M. Moyano, Luciano Sánchez

Proceedings of the 2016 IEEE International Conference on Fuzzy Systems, 2016