A review of feature selection techniques in bioinformatics Y Saeys, I Inza, P Larranaga bioinformatics 23 (19), 2507-2517, 2007 | 6142 | 2007 |
Genetic algorithms for the travelling salesman problem: A review of representations and operators P Larranaga, CMH Kuijpers, RH Murga, I Inza, S Dizdarevic Artificial intelligence review 13, 129-170, 1999 | 1246 | 1999 |
Machine learning in bioinformatics P Larranaga, B Calvo, R Santana, C Bielza, J Galdiano, I Inza, JA Lozano, ... Briefings in bioinformatics 7 (1), 86-112, 2006 | 1112 | 2006 |
Filter versus wrapper gene selection approaches in DNA microarray domains I Inza, P Larranaga, R Blanco, AJ Cerrolaza Artificial intelligence in medicine 31 (2), 91-103, 2004 | 591 | 2004 |
Towards a new evolutionary computation: advances on estimation of distribution algorithms JA Lozano, P Larrañaga, I Inza, E Bengoetxea Springer, 2006 | 485 | 2006 |
Feature subset selection by Bayesian network-based optimization I Inza, P Larrañaga, R Etxeberria, B Sierra Artificial intelligence 123 (1-2), 157-184, 2000 | 375 | 2000 |
Differential micro RNA expression in PBMC from multiple sclerosis patients D Otaegui, SE Baranzini, R Armañanzas, B Calvo, M Muñoz-Culla, ... PloS one 4 (7), e6309, 2009 | 314 | 2009 |
Bayesian classifiers based on kernel density estimation: Flexible classifiers A Pérez, P Larrañaga, I Inza International Journal of Approximate Reasoning 50 (2), 341-362, 2009 | 213 | 2009 |
Supervised classification with conditional Gaussian networks: Increasing the structure complexity from naive Bayes A Perez, P Larranaga, I Inza International Journal of Approximate Reasoning 43 (1), 1-25, 2006 | 173 | 2006 |
Approaching sentiment analysis by using semi-supervised learning of multi-dimensional classifiers J Ortigosa-Hernández, JD Rodríguez, L Alzate, M Lucania, I Inza, ... Neurocomputing 92, 98-115, 2012 | 169 | 2012 |
Dealing with the evaluation of supervised classification algorithms G Santafe, I Inza, JA Lozano Artificial Intelligence Review 44, 467-508, 2015 | 141 | 2015 |
Machine learning: an indispensable tool in bioinformatics I Inza, B Calvo, R Armananzas, E Bengoetxea, P Larranaga, JA Lozano Bioinformatics methods in clinical research, 25-48, 2009 | 140 | 2009 |
A review of estimation of distribution algorithms in bioinformatics R Armañanzas, I Inza, R Santana, Y Saeys, JL Flores, JA Lozano, ... BioData mining 1, 1-12, 2008 | 140 | 2008 |
Gene selection by sequential search wrapper approaches in microarray cancer class prediction I Inza, B Sierra, R Blanco, P Larrañaga Journal of Intelligent & Fuzzy Systems 12 (1), 25-33, 2002 | 133 | 2002 |
Weak supervision and other non-standard classification problems: a taxonomy J Hernández-González, I Inza, JA Lozano Pattern Recognition Letters 69, 49-55, 2016 | 131 | 2016 |
Learning Bayesian networks in the space of structures by estimation of distribution algorithms R Blanco, I Inza, P Larranaga International journal of intelligent systems 18 (2), 205-220, 2003 | 113 | 2003 |
Feature selection in Bayesian classifiers for the prognosis of survival of cirrhotic patients treated with TIPS R Blanco, I Inza, M Merino, J Quiroga, P Larrañaga Journal of Biomedical Informatics 38 (5), 376-388, 2005 | 111 | 2005 |
Gene selection for cancer classification using wrapper approaches R Blanco, P Larrañaga, I Inza, B Sierra International Journal of Pattern Recognition and Artificial Intelligence 18 …, 2004 | 109 | 2004 |
Analyzing rare event, anomaly, novelty and outlier detection terms under the supervised classification framework A Carreño, I Inza, JA Lozano Artificial Intelligence Review 53, 3575-3594, 2020 | 104 | 2020 |
Fish recruitment prediction, using robust supervised classification methods JA Fernandes, X Irigoien, N Goikoetxea, JA Lozano, I Inza, A Pérez, ... Ecological Modelling 221 (2), 338-352, 2010 | 95 | 2010 |