| Sensitivity analysis of k-fold cross validation in prediction error estimation JD Rodriguez, A Perez, JA Lozano IEEE transactions on pattern analysis and machine intelligence 32 (3), 569-575, 2009 | 1894 | 2009 |
| 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 | 1090 | 2006 |
| An efficient approximation to the K-means clustering for massive data M Capó, A Pérez, JA Lozano Knowledge-Based Systems 117, 56-69, 2017 | 254 | 2017 |
| 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 | 208 | 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 | 167 | 2006 |
| 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 | 92 | 2010 |
| An efficient K-means clustering algorithm for tall data M Capó, A Pérez, JA Lozano Data mining and knowledge discovery 34, 776-811, 2020 | 58 | 2020 |
| Using multidimensional bayesian network classifiers to assist the treatment of multiple sclerosis JD Rodriguez, A Perez, D Arteta, D Tejedor, JA Lozano IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and …, 2012 | 41 | 2012 |
| Supervised pre-processing approaches in multiple class variables classification for fish recruitment forecasting JA Fernandes, JA Lozano, I Inza, X Irigoien, A Pérez, JD Rodríguez Environmental modelling & software 40, 245-254, 2013 | 40 | 2013 |
| A general framework for the statistical analysis of the sources of variance for classification error estimators JD Rodríguez, A Pérez, JA Lozano Pattern recognition 46 (3), 855-864, 2013 | 38 | 2013 |
| An Efficient Split-Merge Re-Start for the -Means Algorithm M Capó, A Pérez, JA Lozano IEEE Transactions on Knowledge and Data Engineering 34 (4), 1618-1627, 2020 | 35 | 2020 |
| A Cheap Feature Selection Approach for the K-Means Algorithm M Capó, A Pérez, JA Lozano IEEE transactions on neural networks and learning systems 32 (5), 2195-2208, 2020 | 34 | 2020 |
| On-line dynamic time warping for streaming time series I Oregi, A Pérez, J Del Ser, JA Lozano Machine Learning and Knowledge Discovery in Databases: European Conference …, 2017 | 33 | 2017 |
| Evaluating machine-learning techniques for recruitment forecasting of seven North East Atlantic fish species JA Fernandes, X Irigoien, JA Lozano, I Inza, N Goikoetxea, A Pérez Ecological Informatics 25, 35-42, 2015 | 28 | 2015 |
| An efficient K-means clustering algorithm for massive data M Capó, A Pérez, JA Lozano arXiv preprint arXiv:1801.02949, 2018 | 26 | 2018 |
| Adversarial sample crafting for time series classification with elastic similarity measures I Oregi, J Del Ser, A Perez, JA Lozano Intelligent Distributed Computing XII, 26-39, 2018 | 26 | 2018 |
| How trustworthy is Crafty’s analysis of world chess champions? M Guid, A Pérez, I Bratko ICGA journal 31 (3), 131-144, 2008 | 26 | 2008 |
| On-line elastic similarity measures for time series I Oregi, A Pérez, J Del Ser, JA Lozano Pattern Recognition 88, 506-517, 2019 | 24 | 2019 |
| Generalized maximum entropy for supervised classification S Mazuelas, Y Shen, A Pérez IEEE Transactions on Information Theory 68 (4), 2530-2550, 2022 | 23 | 2022 |
| Minimax Classification with 0-1 Loss and Performance Guarantees S Mazuelas, A Zanoni, A Pérez Neural Information Processing Systems, 2020 | 23 | 2020 |
Jose A. LozanoBasque Center for Applied Mathematics (BCAM), University of the Basque Country UPV/EHUVerified email at ehu.eus
