RAZONAMIENTO APROXIMADO E INTELIGENCIA ARTIFICIAL
RAZONAMIENTO APROXIMADO E INTE
JOAQUÍN
ABELLÁN MULERO
CATEDRÁTICO DE UNIVERSIDAD
Publicaciones en las que colabora con JOAQUÍN ABELLÁN MULERO (26)
2022
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A new label ordering method in Classifier Chains based on imprecise probabilities
Neurocomputing, Vol. 487, pp. 34-45
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Using Credal C4.5 for Calibrated Label Ranking in Multi-Label Classification
International Journal of Approximate Reasoning, Vol. 147, pp. 60-77
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Using extreme prior probabilities on the Naive Credal Classifier
Knowledge-Based Systems, Vol. 237
2021
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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
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Using Credal C4.5 for Calibrated Label Ranking in Multi-Label Classification
Proceedings of Machine Learning Research
2020
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Bagging of credal decision trees for imprecise classification
Expert Systems with Applications, Vol. 141
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Imprecise classification with non-parametric predictive inference
Communications in Computer and Information Science
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Non-parametric predictive inference for solving multi-label classification
Applied Soft Computing Journal, Vol. 88
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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
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A comparison of random forest based algorithms: random credal random forest versus oblique random forest
Soft Computing, Vol. 23, Núm. 21, pp. 10739-10754
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Decision tree ensemble method for analyzing traffic accidents of novice drivers in urban areas
Entropy, Vol. 21, Núm. 4
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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
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AdaptativeCC4.5: Credal C4.5 with a rough class noise estimator
Expert Systems with Applications, Vol. 92, pp. 363-379
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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
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Credal C4.5 with refinement of parameters
Communications in Computer and Information Science
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Increasing diversity in random forest learning algorithm via imprecise probabilities
Expert Systems with Applications, Vol. 97, pp. 228-243
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Using Credal-C4.5 with Binary Relevance for Multi-Label Classification
Journal of Intelligent and Fuzzy Systems
2017
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A New Robust Classifier on Noise Domains: Bagging of Credal C4.5 Trees
Complexity, Vol. 2017
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A Random Forest approach using imprecise probabilities
Knowledge-Based Systems, Vol. 134, pp. 72-84
2016
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Analysis of Credal-C4.5 for classification in noisy domains
Expert Systems with Applications, Vol. 61, pp. 314-326