Publicaciones en las que colabora con FRANCISCO JAVIER GARCÍA CASTELLANO (23)

2022

  1. A new label ordering method in Classifier Chains based on imprecise probabilities

    Neurocomputing, Vol. 487, pp. 34-45

  2. Using Credal C4.5 for Calibrated Label Ranking in Multi-Label Classification

    International Journal of Approximate Reasoning, Vol. 147, pp. 60-77

  3. Using extreme prior probabilities on the Naive Credal Classifier

    Knowledge-Based Systems, Vol. 237

2021

  1. 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

  2. Using Credal C4.5 for Calibrated Label Ranking in Multi-Label Classification

    Proceedings of Machine Learning Research

2020

  1. Bagging of credal decision trees for imprecise classification

    Expert Systems with Applications, Vol. 141

  2. Imprecise classification with non-parametric predictive inference

    Communications in Computer and Information Science

  3. Non-parametric predictive inference for solving multi-label classification

    Applied Soft Computing Journal, Vol. 88

  4. 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

  1. A comparison of random forest based algorithms: random credal random forest versus oblique random forest

    Soft Computing, Vol. 23, Núm. 21, pp. 10739-10754

  2. Decision tree ensemble method for analyzing traffic accidents of novice drivers in urban areas

    Entropy, Vol. 21, Núm. 4

  3. 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

  1. AdaptativeCC4.5: Credal C4.5 with a rough class noise estimator

    Expert Systems with Applications, Vol. 92, pp. 363-379

  2. Credal C4.5 with refinement of parameters

    Communications in Computer and Information Science

  3. Increasing diversity in random forest learning algorithm via imprecise probabilities

    Expert Systems with Applications, Vol. 97, pp. 228-243

  4. Using Credal-C4.5 with Binary Relevance for Multi-Label Classification

    Journal of Intelligent and Fuzzy Systems

2017

  1. A New Robust Classifier on Noise Domains: Bagging of Credal C4.5 Trees

    Complexity, Vol. 2017

  2. A Random Forest approach using imprecise probabilities

    Knowledge-Based Systems, Vol. 134, pp. 72-84

  3. A comparative study on base classifiers in ensemble methods for credit scoring

    Expert Systems with Applications, Vol. 73, pp. 1-10

  4. Extraction of decision rules via imprecise probabilities

    International Journal of General Systems, Vol. 46, Núm. 4, pp. 313-331