Publicaciones en las que colabora con Andrés Ramón Masegosa Arredondo (14)

2014

  1. Classification

    Introduction to Imprecise Probabilities (wiley), pp. 230-257

  2. Classification with decision trees from a nonparametric predictive inference perspective

    Computational Statistics and Data Analysis, Vol. 71, pp. 789-802

2012

  1. Bagging schemes on the presence of class noise in classification

    Expert Systems with Applications, Vol. 39, Núm. 8, pp. 6827-6837

  2. Imprecise classification with credal decision trees

    International Journal of Uncertainty, Fuzziness and Knowlege-Based Systems, Vol. 20, Núm. 5, pp. 763-787

2011

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

    Intelligent Data Analysis, Vol. 15, Núm. 3, pp. 299-318

2010

  1. An ensemble method using credal decision trees

    European Journal of Operational Research, Vol. 205, Núm. 1, pp. 218-226

  2. Bagging decision trees on data sets with classification noise

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

2009

  1. A filter-wrapper method to select variables for the naive bayes classifier based on credal decision trees

    International Journal of Uncertainty, Fuzziness and Knowlege-Based Systems, Vol. 17, Núm. 6, pp. 833-854

  2. An experimental study about simple decision trees for bagging ensemble on datasets with classification noise

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

2008

  1. Requirements for total uncertainty measures in Dempster-Shafer theory of evidence

    International Journal of General Systems, Vol. 37, Núm. 6, pp. 733-747

2007

  1. A semi-naive bayes classifier with grouping of cases

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

  2. Combining decision trees based on imprecise probabilities and uncertainty measures

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

  3. Split criterions for variable selection using decision trees

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

2006

  1. Varying parameter in classification based on imprecise probabilities

    Advances in Soft Computing, Vol. 37, pp. 231-239