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Andres R. Masegosa
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Year
Requirements for total uncertainty measures in Dempster–Shafer theory of evidence
J Abellán, A Masegosa
International journal of general systems 37 (6), 733-747, 2008
812008
A method for integrating expert knowledge when learning Bayesian networks from data
A Cano, AR Masegosa, S Moral
IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) 41 …, 2011
692011
An interactive approach for Bayesian network learning using domain/expert knowledge
AR Masegosa, S Moral
International Journal of Approximate Reasoning 54 (8), 1168-1181, 2013
662013
Bagging schemes on the presence of class noise in classification
J Abellán, AR Masegosa
Expert Systems with Applications 39 (8), 6827-6837, 2012
612012
Bagging decision trees on data sets with classification noise
J Abellán, AR Masegosa
International Symposium on Foundations of Information and Knowledge Systems …, 2010
492010
An ensemble method using credal decision trees
J Abellan, AR Masegosa
European journal of operational research 205 (1), 218-226, 2010
482010
Classification with decision trees from a nonparametric predictive inference perspective
J Abellán, RM Baker, F Coolen, RJ Crossman, AR Masegosa
Computational Statistics & Data Analysis 71, 789-802, 2014
322014
An experimental study about simple decision trees for bagging ensemble on datasets with classification noise
J Abellán, AR Masegosa
European Conference on Symbolic and Quantitative Approaches to Reasoning and …, 2009
302009
Learning from incomplete data in Bayesian networks with qualitative influences
AR Masegosa, AJ Feelders, LC van der Gaag
International Journal of Approximate Reasoning 69, 18-34, 2016
292016
Learning under Model Misspecification: Applications to Variational and Ensemble methods
A Masegosa
Advances in Neural Information Processing Systems 33, 2020
252020
New skeleton-based approaches for Bayesian structure learning of Bayesian networks
AR Masegosa, S Moral
Applied Soft Computing 13 (2), 1110-1120, 2013
252013
Modeling concept drift: A probabilistic graphical model based approach
H Borchani, AM Martínez, AR Masegosa, H Langseth, TD Nielsen, ...
International Symposium on Intelligent Data Analysis, 72-83, 2015
242015
Bayesian models of data streams with hierarchical power priors
A Masegosa, TD Nielsen, H Langseth, D Ramos-López, A Salmerón, ...
Proceedings of the 34th International Conference on Machine Learning-Volume …, 2017
222017
AMIDST: A Java toolbox for scalable probabilistic machine learning
AR Masegosa, AM Martínez, D Ramos-López, R Cabañas, A Salmerón, ...
Knowledge-Based Systems 163, 595-597, 2019
212019
Second order PAC-Bayesian bounds for the weighted majority vote
A Masegosa, S Lorenzen, C Igel, Y Seldin
Advances in Neural Information Processing Systems 33, 2020
202020
Imprecise classification with credal decision trees
J Abellan, AR Masegosa
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems …, 2012
182012
Probabilistic Graphical Models on Multi-Core CPUs Using Java 8
AR Masegosa, AM Martinez, H Borchani
IEEE Computational Intelligence Magazine 11 (2), 41-54, 2016
172016
Locally averaged Bayesian Dirichlet metrics for learning the structure and the parameters of Bayesian networks
A Cano, M Gómez-Olmedo, AR Masegosa, S Moral
International Journal of Approximate Reasoning 54 (4), 526-540, 2013
162013
A filter-wrapper method to select variables for the naive bayes classifier based on credal decision trees
J ABELLÁN, AR Masegosa, M Gómez
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems …, 2009
162009
Imprecise probability models for learning multinomial distributions from data. Applications to learning credal networks
AR Masegosa, S Moral
International Journal of Approximate Reasoning 55 (7), 1548-1569, 2014
152014
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Articles 1–20