Dependent binary relevance models for multi-label classification E Montanes, R Senge, J Barranquero, JR Quevedo, JJ del Coz, ... Pattern Recognition 47 (3), 1494-1508, 2014 | 162 | 2014 |
A SVM-based regression model to study the air quality at local scale in Oviedo urban area (Northern Spain): A case study PJG Nieto, EF Combarro, JJ del Coz Díaz, E Montañés Applied Mathematics and Computation 219 (17), 8923-8937, 2013 | 136 | 2013 |
Introducing a family of linear measures for feature selection in text categorization EF Combarro, E Montanes, I Diaz, J Ranilla, R Mones IEEE transactions on Knowledge and Data Engineering 17 (9), 1223-1232, 2005 | 120 | 2005 |
Scoring and selecting terms for text categorization E Montanes, I Diaz, J Ranilla, EF Combarro, J Fernandez IEEE Intelligent Systems 20 (3), 40-47, 2005 | 66 | 2005 |
Power plant condenser performance forecasting using a non-fully connected artificial neural network MM Prieto, E Montanes, O Menendez Energy 26 (1), 65-79, 2001 | 60 | 2001 |
Improving performance of text categorization by combining filtering and support vector machines I Díaz, J Ranilla, E Montañes, J Fernández, EF Combarro Journal of the American society for information science and technology 55 (7 …, 2004 | 47 | 2004 |
Analysis of the thermal performance of a church window steam condenser for different operational conditions using three models MM Prieto, IM Suarez, E Montanes Applied thermal engineering 23 (2), 163-178, 2003 | 46 | 2003 |
Aggregating independent and dependent models to learn multi-label classifiers E Montanés, JR Quevedo, JJ del Coz Joint European Conference on Machine Learning and Knowledge Discovery in …, 2011 | 34 | 2011 |
Measures of rule quality for feature selection in text categorization E Montanés, J Fernández, I Díaz, EF Combarro, J Ranilla international Symposium on Intelligent data analysis, 589-598, 2003 | 33 | 2003 |
Enhancing directed binary trees for multi-class classification E Montañés, J Barranquero, J Díez, JJ Del Coz Information Sciences 223, 42-55, 2013 | 28 | 2013 |
Using A* for inference in probabilistic classifier chains D Mena Waldo, E Montañés Roces, JR Quevedo Pérez, JJ Coz Velasco Proceedings of the Twenty-Fourth International Joint Conference on …, 2015 | 25 | 2015 |
A wrapper approach with support vector machines for text categorization E Montañés, JR Quevedo, I Díaz International Work-Conference on Artificial Neural Networks, 230-237, 2003 | 25 | 2003 |
An overview of inference methods in probabilistic classifier chains for multilabel classification D Mena, E Montañés, JR Quevedo, JJ del Coz Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 6 (6 …, 2016 | 23 | 2016 |
Forecasting time series combining machine learning and box-jenkins time series E Montañés, JR Quevedo, MM Prieto, CO Menéndez Advances in Artificial Intelligence—IBERAMIA 2002: 8th Ibero-American …, 2002 | 23 | 2002 |
Collaborative tag recommendation system based on logistic regression E Montanés, JR Quevedo, I Díaz, J Ranilla ECML PKDD Discovery Challenge, 173-188, 2009 | 19 | 2009 |
Towards automatic and optimal filtering levels for feature selection in text categorization E Montañés, EF Combarro, I Díaz, J Ranilla Advances in Intelligent Data Analysis VI: 6th International Symposium on …, 2005 | 17 | 2005 |
Ordinal classification/regression for analyzing the influence of superstars on spectators in cinema marketing E Montañés, A Suárez-Vázquez, JR Quevedo Expert Systems with Applications 41 (18), 8101-8111, 2014 | 16 | 2014 |
Obtaining Rubric Weights for Assessments by More than One Lecturer Using a Pairwise Learning Model. JR Quevedo, E Montañés International Working Group on Educational Data Mining, 2009 | 16 | 2009 |
Waste heat recovery system for marine engines optimized through a preference learning rank function embedded into a Bayesian optimizer LA Díaz-Secades, R González, N Rivera, E Montañés, JR Quevedo Ocean Engineering 281, 114747, 2023 | 11 | 2023 |
Adapting decision DAGs for multipartite ranking JR Quevedo, E Montanés, O Luaces, JJ Del Coz Joint European Conference on Machine Learning and Knowledge Discovery in …, 2010 | 11 | 2010 |