CARLOS JAVIER
MANTAS RUIZ
CATEDRÁTICO DE UNIVERSIDAD
SERAFÍN
MORAL GARCÍA
PROFESOR AYUDANTE DOCTOR (LOSU)
Publicaciones en las que colabora con SERAFÍN MORAL GARCÍA (14)
2022
-
A new label ordering method in Classifier Chains based on imprecise probabilities
Neurocomputing, Vol. 487, pp. 34-45
-
Using Credal C4.5 for Calibrated Label Ranking in Multi-Label Classification
International Journal of Approximate Reasoning, Vol. 147, pp. 60-77
-
Using extreme prior probabilities on the Naive Credal Classifier
Knowledge-Based Systems, Vol. 237
2021
-
A Decision Support Tool for Credit Domains: Bayesian Network with a Variable Selector Based on Imprecise Probabilities
International Journal of Fuzzy Systems, Vol. 23, Núm. 7, pp. 2004-2020
-
Using Credal C4.5 for Calibrated Label Ranking in Multi-Label Classification
Proceedings of Machine Learning Research
2020
-
Bagging of credal decision trees for imprecise classification
Expert Systems with Applications, Vol. 141
-
Non-parametric predictive inference for solving multi-label classification
Applied Soft Computing Journal, Vol. 88
-
On the Use of m-Probability-Estimation and Imprecise Probabilities in the Naïve Bayes Classifier
International Journal of Uncertainty, Fuzziness and Knowlege-Based Systems, Vol. 28, Núm. 4, pp. 661-682
2019
-
A comparison of random forest based algorithms: random credal random forest versus oblique random forest
Soft Computing, Vol. 23, Núm. 21, pp. 10739-10754
-
Decision tree ensemble method for analyzing traffic accidents of novice drivers in urban areas
Entropy, Vol. 21, Núm. 4
-
Ensemble of classifier chains and Credal C4.5 for solving multi-label classification
Progress in Artificial Intelligence, Vol. 8, Núm. 2, pp. 195-213
2018
-
Credal C4.5 with refinement of parameters
Information Processing and Management of Uncertainty in Knowledge-Based Systems. Applications: 17th International Conference, IPMU 2018, Cádiz, Spain, June 11-15, 2018, Proceedings, Part III
-
Increasing diversity in random forest learning algorithm via imprecise probabilities
Expert Systems with Applications, Vol. 97, pp. 228-243
-
Using Credal-C4.5 with Binary Relevance for Multi-Label Classification
Journal of Intelligent and Fuzzy Systems