| Handling numeric attributes when comparing Bayesian network classifiers: does the discretization method matter? MJ Flores, JA Gámez, AM Martínez, JM Puerta Applied Intelligence 34 (3), 372-385, 2011 | 42 | 2011 |
| Scalable Learning of Bayesian Network Classifiers AM Martinez, GI Webb, S Chen, NA Zaidi Journal of Machine Learning Research 17, 1-35, 2016 | 31 | 2016 |
| GAODE and HAODE: two proposals based on AODE to deal with continuous variables MJ Flores, JA Gámez, AM Martínez, JM Puerta Proceedings of the 26th annual international conference on machine learning …, 2009 | 24 | 2009 |
| Domains of competence of the semi-naive Bayesian network classifiers MJ Flores, JA Gámez, AM Martínez Information Sciences 260, 120-148, 2014 | 19 | 2014 |
| 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 | 16 | 2015 |
| HODE: Hidden one-dependence estimator MJ Flores, JA Gámez, AM Martínez, JM Puerta European Conference on Symbolic and Quantitative Approaches to Reasoning and …, 2009 | 14 | 2009 |
| Parallel importance sampling in conditional linear Gaussian networks A Salmerón, D Ramos-López, H Borchani, AM Martínez, AR Masegosa, ... Conference of the Spanish Association for Artificial Intelligence, 36-46, 2015 | 12 | 2015 |
| Supervised Classification with Bayesian Networks: A Review on Models and Applications MJ Flores, JA Gámez, AM Martínez Intelligent Data Analysis for Real-Life Applications: Theory and Practice …, 2012 | 12 | 2012 |
| AMIDST: A Java toolbox for scalable probabilistic machine learning AR Masegosa, AM Martínez, D Ramos-López, R Cabańas, A Salmerón, ... Knowledge-Based Systems 163, 595-597, 2019 | 10 | 2019 |
| Scaling up Bayesian variational inference using distributed computing clusters AR Masegosa, AM Martinez, H Langseth, TD Nielsen, A Salmerón, ... International Journal of Approximate Reasoning 88, 435-451, 2017 | 10 | 2017 |
| 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 | 10 | 2016 |
| Selective AnDE for large data learning: a low-bias memory constrained approach S Chen, AM Martínez, GI Webb, L Wang Knowledge and Information Systems 50 (2), 475-503, 2017 | 9 | 2017 |
| Dynamic Bayesian modeling for risk prediction in credit operations. H Borchani, AM Martínez, AR Masegosa, H Langseth, TD Nielsen, ... SCAI, 17-26, 2015 | 9 | 2015 |
| Mixture of truncated exponentials in supervised classification: Case study for the naive Bayes and averaged one-dependence estimators classifiers MJ Flores, JA Gámez, AM Martínez, A Salmerón 2011 11th International Conference on Intelligent Systems Design and …, 2011 | 8 | 2011 |
| Sample-Based Attribute Selective A DE for Large Data S Chen, AM Martinez, GI Webb, L Wang IEEE Transactions on Knowledge and Data Engineering 29 (1), 172-185, 2016 | 7 | 2016 |
| Highly scalable attribute selection for averaged one-dependence estimators S Chen, AM Martinez, GI Webb Pacific-Asia Conference on Knowledge Discovery and Data Mining, 86-97, 2014 | 7 | 2014 |
| d-VMP: Distributed Variational Message Passing AR Masegosa, AM Martínez, H Langseth, TD Nielsen, A Salmerón, ... Proceedings of the Eighth International Conference on Probabilistic …, 2016 | 6 | 2016 |
| Analyzing the impact of the discretization method when comparing Bayesian classifiers MJ Flores, JA Gámez, AM Martínez, JM Puerta International Conference on Industrial, Engineering and Other Applications …, 2010 | 6 | 2010 |
| MAP inference in dynamic hybrid Bayesian networks D Ramos-López, AR Masegosa, AM Martínez, A Salmerón, TD Nielsen, ... Progress in Artificial Intelligence 6 (2), 133-144, 2017 | 4 | 2017 |
| HODE AM Martínez | 4 | 2017 |
Andres R. MasegosaUniversity of AlmeriaVerified email at ual.es
