Publicaciones (87) Publicaciones de JOAQUÍN ABELLÁN MULERO

2023

  1. A Variation of the Algorithm to Achieve the Maximum Entropy for Belief Functions

    Entropy, Vol. 25, Núm. 6

  2. Improving the Results in Credit Scoring by Increasing Diversity in Ensembles of Classifiers

    IEEE Access, Vol. 11, pp. 58451-58461

  3. Upgrading the Fusion of Imprecise Classifiers

    Entropy, Vol. 25, Núm. 7

2022

  1. A cost-sensitive Imprecise Credal Decision Tree based on Nonparametric Predictive Inference

    Applied Soft Computing, Vol. 123

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

    Neurocomputing, Vol. 487, pp. 34-45

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

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

  4. 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. Basic Probability Assignments Representable via Belief Intervals for Singletons in Dempster-Shafer Theory

    Proceedings of Machine Learning Research

  3. Combination in the theory of evidence via a new measurement of the conflict between evidences

    Expert Systems with Applications, Vol. 178

  4. Credal sets representable by reachable probability intervals and belief functions

    International Journal of Approximate Reasoning, Vol. 129, pp. 84-102

  5. Required mathematical properties and behaviors of uncertainty measures on belief intervals

    International Journal of Intelligent Systems, Vol. 36, Núm. 8

  6. Uncertainty-based information measures on the approximate non-parametric predictive inference model

    International Journal of General Systems, Vol. 50, Núm. 2, pp. 159-181

  7. 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. Critique of Recent Uncertainty Measures Developed Under the Evidence Theory and Belief Intervals

    IEEE Transactions on Systems, Man, and Cybernetics: Systems, Vol. 50, Núm. 3, pp. 1186-1192

  3. Critique of modified Deng entropies under the evidence theory

    Chaos, Solitons and Fractals, Vol. 140

  4. Imprecise classification with non-parametric predictive inference

    Communications in Computer and Information Science

  5. Maximum of Entropy for Belief Intervals under Evidence Theory

    IEEE Access, Vol. 8, pp. 118017-118029

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

    Applied Soft Computing Journal, Vol. 88