Joaquín Abellán

发表

Imprecise Classification with Credal Decision Trees

Andrés R. Masegosa, Joaquín Abellán, 2012, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

Improving the Naive Bayes Classifier via a Quick Variable Selection Method Using Maximum of Entropy

Francisco Javier García Castellano, Joaquín Abellán, J. Abellán, 2017, Entropy.

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

Francisco Javier García Castellano, Joaquín Abellán, Carlos Javier Mantas, 2020, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

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

Francisco Javier García Castellano, Joaquín Abellán, Carlos Javier Mantas, 2017, Complex..

Application of uncertainty measures on credal sets on the naive Bayesian classifier

Joaquín Abellán, 2006, Int. J. Gen. Syst..

Patterns of Single-Vehicle Crashes on Two-Lane Rural Highways in Granada Province, Spain

Griselda López, Joaquín Abellán, Alfonso Montella, 2014 .

Improving experimental studies about ensembles of classifiers for bankruptcy prediction and credit scoring

Joaquín Abellán, Carlos Javier Mantas, J. Abellán, 2014, Expert Syst. Appl..

Ensemble of classifier chains and Credal C4.5 for solving multi-label classification

Francisco Javier García Castellano, Joaquín Abellán, Carlos Javier Mantas, 2019, Progress in Artificial Intelligence.

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

Francisco Javier García Castellano, Joaquín Abellán, Carlos Javier Mantas, 2018, Soft Computing.

Split Criterions for Variable Selection Using Decision Trees

Andrés R. Masegosa, Joaquín Abellán, 2007, ECSQARU.

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

Eloi Bosse, Joaquín Abellán, 2020, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

An Experimental Study about Simple Decision Trees for Bagging Ensemble on Datasets with Classification Noise

Andrés R. Masegosa, Joaquín Abellán, A. Masegosa, 2009, ECSQARU.

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

Francisco Javier García Castellano, Joaquín Abellán, Carlos Javier Mantas, 2019, Entropy.

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

Francisco Javier García Castellano, Joaquín Abellán, Carlos Javier Mantas, 2018, J. Intell. Fuzzy Syst..

Maximum of Entropy for Belief Intervals Under Evidence Theory

Joaquín Abellán, Serafín Moral-García, J. Abellán, 2020, IEEE Access.

New Score for Independence Based on the Imprecise Dirichlet Model

Serafín Moral, Joaquín Abellán, S. Moral, 2005, ISIPTA.

Upper entropy of credal sets. Applications to credal classification

Serafín Moral, Joaquín Abellán, S. Moral, 2005, Int. J. Approx. Reason..

Measures of divergence on credal sets

Joaquín Abellán, Manuel Gómez-Olmedo, 2006, Fuzzy Sets Syst..

Determining dependence relations using a new score based on imprecise probabilities

Serafín Moral, Joaquín Abellán, S. Moral, 2012, Intell. Data Anal..

Credal C4.5 with Refinement of Parameters

Serafín Moral, Francisco Javier García Castellano, Joaquín Abellán, 2018, IPMU.

A Non-Specificity Measure for Convex Sets of Probability Distributions

Serafín Moral, Joaquín Abellán, S. Moral, 2000, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

Credal-C4.5: Decision tree based on imprecise probabilities to classify noisy data

Joaquín Abellán, Carlos Javier Mantas, J. Abellán, 2014, Expert Syst. Appl..

A Semi-naive Bayes Classifier with Grouping of Cases

Andrés R. Masegosa, Serafín Moral, Joaquín Abellán, 2007, ECSQARU.

Book review

Joaquín Abellán, 2006, Fuzzy Sets Syst..

Bagging schemes on the presence of class noise in classification

Andrés R. Masegosa, Joaquín Abellán, A. Masegosa, 2012, Expert Syst. Appl..

A Non-Specificity Measure for Convex Sets of Probability Distributions

Serafín Moral, Joaquín Abellán, S. Moral, 2000, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

Bagging of credal decision trees for imprecise classification

Francisco Javier García Castellano, Joaquín Abellán, Carlos Javier Mantas, 2020, Expert Syst. Appl..

Some Variations on the PC Algorithm

Joaquín Abellán, Serafín Moral, Manuel Gómez-Olmedo, 2006, Probabilistic Graphical Models.

Basic Properties for Total Uncertainty Measures in the Theory of Evidence

Éloi Bossé, Joaquín Abellán, Carlos Javier Mantas, 2019, Information Quality in Information Fusion and Decision Making.

A Random Forest approach using imprecise probabilities

Francisco Javier García Castellano, Joaquín Abellán, Carlos Javier Mantas, 2017, Knowl. Based Syst..

Varying Parameter in Classification Based on Imprecise Probabilities

Andrés R. Masegosa, Serafín Moral, Joaquín Abellán, 2006, SMPS.

Maximum of Entropy for Credal Sets

Serafín Moral, Joaquín Abellán, 2003, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

Analysis and extension of decision trees based on imprecise probabilities: Application on noisy data

Joaquín Abellán, Carlos Javier Mantas, J. Abellán, 2014, Expert Syst. Appl..

Using Imprecise Probabilities to Extract Decision Rules via Decision Trees for Analysis of Traffic Accidents

Laura Garach, Francisco Javier García Castellano, Joaquín Abellán, 2014, RSCTC.

Requirements for total uncertainty measures in Dempster–Shafer theory of evidence

Andrés R. Masegosa, Joaquín Abellán, A. Masegosa, 2008, Int. J. Gen. Syst..

Equivalence relations among dominance concepts on probability intervals and general credal sets

Joaquín Abellán, 2012, Int. J. Gen. Syst..

An application of Non-Parametric Predictive Inference on multi-class classification high-level-noise problems

Joaquín Abellán, 2013, Expert Syst. Appl..

Imprecise Classification with Non-parametric Predictive Inference

Francisco Javier García Castellano, Joaquín Abellán, Carlos Javier Mantas, 2020, IPMU.

A Filter-Wrapper Method to Select Variables for the Naive Bayes Classifier Based on Credal Decision Trees

Andrés R. Masegosa, Joaquín Abellán, 2009, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

Non-parametric predictive inference for solving multi-label classification

Francisco Javier García Castellano, Joaquín Abellán, Carlos Javier Mantas, 2020, Appl. Soft Comput..

Uncertainty measures on probability intervals from the imprecise Dirichlet model

Joaquín Abellán, 2006, Int. J. Gen. Syst..

A memory efficient semi-Naive Bayes classifier with grouping of cases

Andrés R. Masegosa, Serafín Moral, Joaquín Abellán, 2011, Intell. Data Anal..

Bagging Decision Trees on Data Sets with Classification Noise

Andrés R. Masegosa, Joaquín Abellán, A. Masegosa, 2010, FoIKS.

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

Joaquín Abellán, Serafín Moral-García, María Dolores Benítez, 2019, ECSQARU.

Extracting decision rules from police accident reports through decision trees.

Griselda López, Joaquín Abellán, Juan de Oña, 2013, Accident; analysis and prevention.

Combining Decision Trees Based on Imprecise Probabilities and Uncertainty Measures

Andrés R. Masegosa, Joaquín Abellán, A. Masegosa, 2007, ECSQARU.

Credal Decision Trees to Classify Noisy Data Sets

Joaquín Abellán, Carlos Javier Mantas, J. Abellán, 2014, HAIS.

Classification with decision trees from a nonparametric predictive inference perspective

Frank P. A. Coolen, Andrés R. Masegosa, Joaquín Abellán, 2014, Comput. Stat. Data Anal..

Maximising entropy on the nonparametric predictive inference model for multinomial data

Frank P. A. Coolen, Joaquín Abellán, Rebecca M. Baker, 2011, Eur. J. Oper. Res..

Extraction of decision rules via imprecise probabilities

Laura Garach, Francisco Javier García Castellano, Joaquín Abellán, 2017, Int. J. Gen. Syst..

Hill-climbing and branch-and-bound algorithms for exact and approximate inference in credal networks

Serafín Moral, Joaquín Abellán, Andrés Cano, 2007, Int. J. Approx. Reason..

Expert Systems With Applications

Francisco Javier García Castellano, Joaquín Abellán, J. Abellán, 2022 .

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

Francisco Javier García Castellano, Joaquín Abellán, Carlos Javier Mantas, 2018, Expert Syst. Appl..

An ensemble method using credal decision trees

Andrés R. Masegosa, Joaquín Abellán, A. Masegosa, 2010, Eur. J. Oper. Res..

Disaggregated total uncertainty measure for credal sets

George J. Klir, Serafín Moral, Joaquín Abellán, 2006, Int. J. Gen. Syst..

Credal decision trees in noisy domains

Joaquín Abellán, Carlos Javier Mantas, 2014, ESANN.

Building classification trees using the total uncertainty criterion

Serafín Moral, Joaquín Abellán, S. Moral, 2003, Int. J. Intell. Syst..

Analysis of Credal-C4.5 for classification in noisy domains

Francisco Javier García Castellano, Joaquín Abellán, Carlos Javier Mantas, 2016, Expert Syst. Appl..

An Algorithm to Compute the Upper Entropy for Order-2 Capacities

Serafín Moral, Joaquín Abellán, 2006, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

Critique of modified Deng entropies under the evidence theory

Joaquín Abellán, Serafín Moral-García, J. Abellán, 2020 .

Ensembles of decision trees based on imprecise probabilities and uncertainty measures

Joaquín Abellán, J. Abellán, 2013, Inf. Fusion.

Additivity of uncertainty measures on credal sets

George J. Klir, Joaquín Abellán, 2005, Int. J. Gen. Syst..

Drawbacks of Uncertainty Measures Based on the Pignistic Transformation

Éloi Bossé, Joaquín Abellán, 2018, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

Maximum of Entropy in Credal Classification

Serafín Moral, Joaquín Abellán, S. Moral, 2003, ISIPTA.

Increasing diversity in random forest learning algorithm via imprecise probabilities

Serafín Moral, Francisco Javier García Castellano, Joaquín Abellán, 2018, Expert Syst. Appl..

Analysis of traffic accident severity using Decision Rules via Decision Trees

Juan de Oña, Joaquín Abellán, Griselda López, 2013, Expert Syst. Appl..

Combining nonspecificity measures in Dempster–Shafer theory of evidence

Joaquín Abellán, 2011, Int. J. Gen. Syst..

Difference of entropies as a non-specificity function on credal sets†

Serafín Moral, Joaquín Abellán, 2005, Int. J. Gen. Syst..

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

Joaquín Abellán, Serafín Moral-García, María D. Benítez, 2021, Expert Syst. Appl..

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

Joaquín Abellán, Serafín Moral-García, 2021, Int. J. Gen. Syst..

Required mathematical properties and behaviors of uncertainty measures on belief intervals

Joaquín Abellán, Serafín Moral-García, J. Abellán, 2021, Int. J. Intell. Syst..

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

Francisco Javier García Castellano, Joaquín Abellán, Carlos Javier Mantas, 2021, International Journal of Fuzzy Systems.

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

Joaquín Abellán, Serafín Moral-García, J. Abellán, 2021, ISIPTA.

Credal sets representable by reachable probability intervals and belief functions

Joaquín Abellán, Serafín Moral-García, J. Abellán, 2021, Int. J. Approx. Reason..

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

Francisco Javier García Castellano, Joaquín Abellán, Carlos Javier Mantas, 2022, ISIPTA.

Remarks on “A new non-specificity measure in evidence theory based on belief intervals”

Joaquín Abellán, 2017 .

Range of Entropy for Credal Sets

Serafín Moral, Joaquín Abellán, S. Moral, 2004 .

Analyzing properties of Deng entropy in the theory of evidence

Joaquín Abellán, J. Abellán, 2017 .

A non-specificity measure for convex sets of probability distributions

Serafín Moral, Joaquín Abellán, S. Moral, 2000 .