A comparative study on base classifiers in ensemble methods for credit scoring J Abellán, JG Castellano Expert systems with applications 73, 1-10, 2017 | 303 | 2017 |
Elvira: An environment for creating and using probabilistic graphical models Elvira Consortium Proceedings of the first European workshop on probabilistic graphical models …, 2002 | 184 | 2002 |
Bayesian network learning algorithms using structural restrictions LM de Campos, JG Castellano International Journal of Approximate Reasoning 45 (2), 233-254, 2007 | 146 | 2007 |
Evolving RBF neural networks for time-series forecasting with EvRBF VM Rivas, JJ Merelo, PA Castillo, MG Arenas, JG Castellano Information Sciences 165 (3-4), 207-220, 2004 | 141 | 2004 |
Learning Bayesian network classifiers: Searching in a space of partially directed acyclic graphs S Acid, LM de Campos, JG Castellano Machine learning 59, 213-235, 2005 | 99 | 2005 |
A comparison of random forest based algorithms: random credal random forest versus oblique random forest JA Carlos J. Mantas, Javier G. Castellano, Serafín Moral-García Soft Computing 23, 10739–10754, 2018 | 90* | 2018 |
A random forest approach using imprecise probabilities J Abellán, CJ Mantas, JG Castellano Knowledge-Based Systems 134, 72-84, 2017 | 75 | 2017 |
Improving the Naive Bayes Classifier via a Quick Variable Selection Method Using Maximum of Entropy J Abellán, JG Castellano Entropy 19 (16), 2017 | 66 | 2017 |
Increasing diversity in Random Forest learning algorithm via imprecise probabilities J Abellán, CJ Mantas, JG Castellano, S Moral-García Expert Systems with Applications 97, 228-243, 2018 | 57 | 2018 |
Analysis of Credal-C4. 5 for classification in noisy domains CJ Mantas, J Abellán, JG Castellano Expert Systems with Applications 61, 314-326, 2016 | 54 | 2016 |
Bagging of credal decision trees for imprecise classification S Moral-García, CJ Mantas, JG Castellano, MD Benítez, J Abellan Expert Systems with Applications 141, 112944, 2020 | 51 | 2020 |
Decision tree ensemble method for analyzing traffic accidents of novice drivers in urban areas S Moral-García, JG Castellano, CJ Mantas, A Montella, J Abellán Entropy 21 (4), 360, 2019 | 45 | 2019 |
Bayesian networks classifiers for gene-expression data LM De Campos, A Cano, JG Castellano, S Moral 2011 11th International Conference on Intelligent Systems Design and …, 2011 | 45 | 2011 |
AdaptativeCC4. 5: Credal C4. 5 with a rough class noise estimator J Abellán, CJ Mantas, JG Castellano Expert Systems with Applications 92, 363-379, 2018 | 28 | 2018 |
Lamarckian evolution and the Baldwin effect in evolutionary neural networks PA Castillo, MG Arenas, JG Castellano, JJ Merelo, A Prieto, V Rivas, ... arXiv preprint cs/0603004, 2006 | 26* | 2006 |
Ensemble of classifier chains and Credal C4. 5 for solving multi-label classification S Moral-García, CJ Mantas, JG Castellano, J Abellán Progress in Artificial Intelligence 8, 195-213, 2019 | 19 | 2019 |
Function approximation with evolved multilayer perceptrons PA Castillo, MG Arenas, JG Castellano, M Cillero, JJ Merelo, A Prieto, ... Advances in Neural Networks and Applications, 195-200, 2001 | 19 | 2001 |
Genetic algorithm visualization using self-organizing maps G Romero, JJ Merelo, PA Castillo, JG Castellano, MG Arenas Parallel Problem Solving from Nature—PPSN VII: 7th International Conference …, 2002 | 18 | 2002 |
Combining gene expression data and prior knowledge for inferring gene regulatory networks via Bayesian networks using structural restrictions LM de Campos, A Cano, JG Castellano, S Moral Statistical Applications in Genetics and Molecular Biology, 2019 | 17 | 2019 |
Using credal c4. 5 for calibrated label ranking in multi-label classification S Moral-García, CJ Mantas, JG Castellano, J Abellán International Journal of Approximate Reasoning 147, 60-77, 2022 | 15 | 2022 |