KEEL 3.0: an open source software for multi-stage analysis in data mining I Triguero, S González, JM Moyano, S García López, J Alcalá Fernández, ... International Journal of Computational Intelligence Systems 10, 1238-1249, 2017 | 213 | 2017 |
Review of ensembles of multi-label classifiers: models, experimental study and prospects JM Moyano, EL Gibaja, KJ Cios, S Ventura Information Fusion 44, 33-45, 2018 | 120 | 2018 |
MLDA: A tool for analyzing multi-label datasets JM Moyano, EL Gibaja, S Ventura Knowledge-Based Systems 121, 1-3, 2017 | 27 | 2017 |
An evolutionary approach to build ensembles of multi-label classifiers JM Moyano, EL Gibaja, KJ Cios, S Ventura Information Fusion 50, 168-180, 2019 | 22 | 2019 |
An evolutionary algorithm for optimizing the target ordering in ensemble of regressor chains JM Moyano, EL Gibaja, S Ventura 2017 IEEE congress on evolutionary computation (CEC), 2015-2021, 2017 | 22 | 2017 |
Combining multi-label classifiers based on projections of the output space using Evolutionary algorithms JM Moyano, EL Gibaja, KJ Cios, S Ventura Knowledge-Based Systems 196, 105770, 2020 | 11 | 2020 |
An ensemble-based approach for multi-view multi-label classification EL Gibaja, JM Moyano, S Ventura Progress in Artificial Intelligence 5 (4), 251-259, 2016 | 11 | 2016 |
RKEEL: using KEEL in R code J Moyano, L Sanchez 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 257-264, 2016 | 8 | 2016 |
Performing multi-target regression via gene expression programming-based ensemble models JM Moyano, O Reyes, HM Fardoun, S Ventura Neurocomputing 432, 275-287, 2021 | 7 | 2021 |
Tree-shaped ensemble of multi-label classifiers using grammar-guided genetic programming JM Moyano, EL Gibaja, KJ Cios, S Ventura 2020 IEEE Congress on Evolutionary Computation (CEC), 1-8, 2020 | 4 | 2020 |
Auto-adaptive grammar-guided genetic programming algorithm to build ensembles of multi-label classifiers JM Moyano, S Ventura Information Fusion 78, 1-19, 2022 | 3 | 2022 |
Speeding Up Classifier Chains in Multi-label Classification. JM Moyano, E Gibaja, S Ventura, A Cano IoTBDS, 29-37, 2019 | 3 | 2019 |
Classification accuracy of hepatitis C virus infection outcome: data mining approach M Frias, JM Moyano, A Rivero-Juarez, JM Luna, Á Camacho, HM Fardoun, ... Journal of Medical Internet Research 23 (2), e18766, 2021 | 1 | 2021 |
A gene expression programming method for multi-target regression O Reyes, JM Moyano, JM Luna, S Ventura Proceedings of the International Conference on Learning and Optimization …, 2018 | 1 | 2018 |
Mining association rules in R using the package RKEEL O Sánchez, JM Moyano, L Sánchez, J Alcála-Fádez 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 1-6, 2017 | 1 | 2017 |
Improving the Performance of Multi-Label Classifiers via Label Space Reduction JM Moyano, JM Luna, S Ventura 2022 IEEE International Conference on Omni-layer Intelligent Systems (COINS), 2022 | | 2022 |
Reducing the Label Space a Predefined Ratio for a More Efficient Multilabel Classification JM Moyano, JM Luna, S Ventura IEEE Access 10, 76480-76492, 2022 | | 2022 |
Generating Ensembles of Multi-Label Classifiers Using Cooperative Coevolutionary Algorithms JM Moyano, EL Gibaja, KJ Cios, S Ventura ECAI 2020, 1379-1386, 2020 | | 2020 |
Multi-label classification models for heterogeneous data: an ensemble-based approach. JM Moyano Murillo | | 2020 |
Extraccion de factores relevantes en el análisis de datos biomédicos: una metodologıa basada en técnicas de aprendizaje supervisado O Reyes, JM Moyano, A Rivero-Juárez, RM Luque, A Rivero, J Castano, ... IX Simposio de Teoría y Aplicaciones de la Minería de Datos, TAMIDA 2018 …, 2018 | | 2018 |