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Joaquín Abellán

Joaquín Abellán

D-Index & Metrics

Computer Science

D-Index
31
Citations
3056
World Ranking
13778
National Ranking
270

Overview

Joaquín Abellán is affiliated with the University of Granada in Spain. Their research primarily focuses on the field of computer science, with a notable concentration in artificial intelligence. Additional subfields of study include management science and operations research, computational theory and mathematics, information systems, and statistics and probability.

Their work addresses various specialized topics such as Bayesian modeling and causal inference, multi-criteria decision making, rough sets and fuzzy logic, imbalanced data classification techniques, data mining algorithms and applications, text and document classification technologies, and machine learning and data classification.

Joaquín Abellán has contributed to several scientific papers including:

  • Combination in the theory of evidence via a new measurement of the conflict between evidences (2021, Expert Systems with Applications)
  • Critique of modified Deng entropies under the evidence theory (2020, Chaos Solitons & Fractals)
  • Using Credal C4.5 for Calibrated Label Ranking in Multi-Label Classification (2022, International Journal of Approximate Reasoning)
  • Required mathematical properties and behaviors of uncertainty measures on belief intervals (2021, International Journal of Intelligent Systems)
  • Maximum of Entropy for Belief Intervals Under Evidence Theory (2020, IEEE Access)

Frequent coauthors collaborating with Joaquín Abellán include Serafín Moral-García, Carlos J. Mantas, Javier G. Castellano, María D. Benítez, and Tahani Coolen-Maturi.

The scientist's research outputs have been published often in venues such as Expert Systems with Applications, International Journal of Approximate Reasoning, IEEE Access, Applied Soft Computing, and Entropy.

Best Publications

  • Analysis of traffic accident severity using Decision Rules via Decision Trees

    JoaquíN AbelláN;Griselda LóPez;Juan De OñA

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

    Joaquín Abellán;Javier G. Castellano

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

    Joaquín Abellán;Carlos J. Mantas

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

    Carlos Javier Mantas;Joaquín Abellán

  • Building Classification Trees Using the Total Uncertainty Criterion

    Joaquín Abellán;Serafín Moral

  • Extracting decision rules from police accident reports through decision trees

    Juan de Oña;Griselda López;Joaquín Abellán

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

    Carlos Javier Mantas;Javier G. Castellano;Serafín Moral-García;Joaquín Abellán

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

    Joaquín Abellán;Andrés R. Masegosa

  • Analyzing properties of Deng entropy in the theory of evidence

    Joaquín Abellán

  • Maximum of entropy for credal sets

    Joaquin Abellan;Serafin Moral

  • Upper entropy of credal sets. Applications to credal classification

    Joaquín Abellán;Serafín Moral

  • A Random Forest approach using imprecise probabilities

    Joaquín Abellán;Carlos Javier Mantas;Javier G. Castellano

  • A non-specificity measure for convex sets of probability distributions

    Joaquin Abellan;Serafin Moral

  • Bagging schemes on the presence of class noise in classification

    Joaquín Abellán;Andrés R. Masegosa

  • Disaggregated total uncertainty measure for credal sets

    Joaquín Abellán;George J. Klir;Serafín Moral

  • Uncertainty measures on probability intervals from the imprecise Dirichlet model

    Joaquín Abellán

  • Increasing diversity in random forest learning algorithm via imprecise probabilities

    Joaquín Abellán;Carlos J. Mantas;Javier G. Castellano;Serafín Moral-García

  • Some Variations on the PC Algorithm.

    Joaquín Abellán;Manuel Gómez-Olmedo;Serafín Moral

  • Bagging Decision Trees on Data Sets with Classification Noise

    Joaquín Abellán;Andrés R. Masegosa

  • An ensemble method using credal decision trees

    Joaquín Abellán;Andrés R. Masegosa

  • COMPLETING A TOTAL UNCERTAINTY MEASURE IN THE DEMPSTER-SHAFER THEORY

    Joaquín Abellán;Serafín Moral

  • Bagging of credal decision trees for imprecise classification

    Serafín Moral-García;Carlos Javier Mantas;Javier G. Castellano;María D. Benítez

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

    Carlos J. Mantas;Joaquín Abellán

Frequent Co-Authors

Serafín Moral
Serafín Moral University of Granada
George J. Klir
George J. Klir Binghamton University

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