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Required mathematical properties and behaviors of uncertainty measures on belief intervals

International journal of intelligent systems, 2021-08, Vol.36 (8), p.n/a

2021

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

Soft computing (Berlin, Germany), 2019-11, Vol.23 (21), p.10739-10754

2019

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

Neurocomputing (Amsterdam), 2022-05, Vol.487, p.34-45

2022

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

IEEE access, 2023, Vol.11, p.58451-58461

2023

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Upgrading the Fusion of Imprecise Classifiers

Entropy (Basel, Switzerland), 2023-07, Vol.25 (7), p.1088

2023

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

Entropy (Basel, Switzerland), 2023-05, Vol.25 (6), p.867

2023

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Lazy Multi-Label Classification algorithms based on Non-Parametric Predictive Inference

Expert systems with applications, 2024-12, Vol.256, p.124921, Article 124921

2024

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Critique of modified Deng entropies under the evidence theory

Chaos, solitons and fractals, 2020-11, Vol.140, p.110112, Article 110112

2020

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Credal sets representable by reachable probability intervals and belief functions

International journal of approximate reasoning, 2021-02, Vol.129, p.84-102

2021

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

Expert systems with applications, 2021-09, Vol.178, p.114987, Article 114987

2021

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

International journal of approximate reasoning, 2022-08, Vol.147, p.60-77

2022

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A Bayesian Imprecise Classification method that weights instances using the error costs

Applied soft computing, 2024-11, Vol.165, p.112080, Article 112080

2024

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Increasing diversity in random forest learning algorithm via imprecise probabilities

Expert systems with applications, 2018-05, Vol.97, p.228-243

2018

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

Applied soft computing, 2022-07, Vol.123, p.108916, Article 108916

2022

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Non-parametric predictive inference for solving multi-label classification

Applied soft computing, 2020-03, Vol.88, p.106011, Article 106011

2020

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

International journal of general systems, 2021-02, Vol.50 (2), p.159-181

2021

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Using extreme prior probabilities on the Naive Credal Classifier

Knowledge-based systems, 2022-02, Vol.237, p.107707, Article 107707

2022

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MPE Computation in Bayesian Networks Using Mini-Bucket and Probability Trees Approximation

International journal of uncertainty, fuzziness, and knowledge-based systems, 2020-10, Vol.28 (5), p.785-805

2020

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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 knowledge-based systems, 2020-08, Vol.28 (4), p.661-682

2020

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Partial Calibrated Multi-label Ranking

Building Bridges Between Soft and Statistical Methodologies for Data Science, 2022, Vol.1433, p.287-294

2022

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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, 2021-10, Vol.23 (7), p.2004-2020

2021

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

Journal of intelligent & fuzzy systems, 2018-01, Vol.35 (6), p.6501-6512

2018

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Combination in Dempster-Shafer Theory Based on a Disagreement Factor Between Evidences

Symbolic and Quantitative Approaches to Reasoning with Uncertainty, p.148-159

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Decision Tree Ensemble Method for Analyzing Traffic Accidents of Novice Drivers in Urban Areas

Entropy (Basel, Switzerland), 2019-04, Vol.21 (4), p.360

2019

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Maximum of Entropy for Belief Intervals Under Evidence Theory

IEEE access, 2020, Vol.8, p.118017-118029

2020

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Required mathematical properties and behaviors of uncertainty measures on belief intervals

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

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

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

Upgrading the Fusion of Imprecise Classifiers

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

Lazy Multi-Label Classification algorithms based on Non-Parametric Predictive Inference

Critique of modified Deng entropies under the evidence theory

Credal sets representable by reachable probability intervals and belief functions

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

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

A Bayesian Imprecise Classification method that weights instances using the error costs

Increasing diversity in random forest learning algorithm via imprecise probabilities

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

Non-parametric predictive inference for solving multi-label classification

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

Using extreme prior probabilities on the Naive Credal Classifier

MPE Computation in Bayesian Networks Using Mini-Bucket and Probability Trees Approximation

On the Use of m -Probability-Estimation and Imprecise Probabilities in the Naïve Bayes Classifier

Partial Calibrated Multi-label Ranking

A Decision Support Tool for Credit Domains: Bayesian Network with a Variable Selector Based on Imprecise Probabilities

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

Combination in Dempster-Shafer Theory Based on a Disagreement Factor Between Evidences

Decision Tree Ensemble Method for Analyzing Traffic Accidents of Novice Drivers in Urban Areas

Maximum of Entropy for Belief Intervals Under Evidence Theory

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