Strategies for learning in class imbalance problems R Barandela, JS Sánchez, V García, E Rangel Pattern Recognition 36 (3), 849-851, 2003 | 734 | 2003 |
On the effectiveness of preprocessing methods when dealing with different levels of class imbalance V García, JS Sánchez, RA Mollineda Knowledge-Based Systems 25 (1), 13-21, 2012 | 419 | 2012 |
The imbalanced training sample problem: Under or over sampling? R Barandela, RM Valdovinos, JS Sanchez, FJ Ferri Structural, Syntactic, and Statistical Pattern Recognition, 806-814, 2004 | 334 | 2004 |
New applications of ensembles of classifiers R Barandela, RM Valdovinos, JS Sánchez Pattern Analysis & Applications 6, 245-256, 2003 | 332 | 2003 |
On the k-NN performance in a challenging scenario of imbalance and overlapping V García, RA Mollineda, JS Sánchez Pattern Analysis and Applications 11, 269-280, 2008 | 264 | 2008 |
Index of balanced accuracy: a performance measure for skewed class distributions V García, R Mollineda, JS Sánchez Pattern Recognition and Image Analysis, 441-448, 2009 | 236 | 2009 |
Analysis of new techniques to obtain quality training sets JS Sánchez, R Barandela, AI Marqués, R Alejo, J Badenas Pattern Recognition Letters 24 (7), 1015-1022, 2003 | 226 | 2003 |
Prototype selection for the nearest neighbour rule through proximity graphs JS Sánchez, F Pla, FJ Ferri Pattern Recognition Letters 18 (6), 507-513, 1997 | 203 | 1997 |
Exploring the behaviour of base classifiers in credit scoring ensembles AI Marqués, V García, JS Sánchez Expert Systems with Applications 39 (11), 10244-10250, 2012 | 201 | 2012 |
On the suitability of resampling techniques for the class imbalance problem in credit scoring AI Marqués, V García, JS Sánchez Journal of the Operational Research Society 64 (7), 1060-1070, 2013 | 169 | 2013 |
A literature review on the application of evolutionary computing to credit scoring AI Marqués, V García, JS Sánchez Journal of the Operational Research Society 64 (9), 1384-1399, 2013 | 148 | 2013 |
An empirical study of the behavior of classifiers on imbalanced and overlapped data sets V García, JS Sánchez, RA Mollineda Progress in Pattern Recognition, Image Analysis and Applications, 397-406, 2007 | 146 | 2007 |
On the use of neighbourhood-based non-parametric classifiers JS Sánchez, F Pla, FJ Ferri Pattern Recognition Letters 18 (11-13), 1179-1186, 1997 | 141 | 1997 |
Two-level classifier ensembles for credit risk assessment AI Marqués, V García, JS Sánchez Expert Systems with Applications 39 (12), 10916-10922, 2012 | 137 | 2012 |
The class imbalance problem in pattern classification and learning JS Sánchez, R Alejo, V García, RA Mollineda, JM Sotoca IV Taller de Minería de Datos y Aprendizaje, 283-291, 2007 | 135* | 2007 |
Exploring the synergetic effects of sample types on the performance of ensembles for credit risk and corporate bankruptcy prediction V García, AI Marqués, JS Sánchez Information Fusion 47, 88-101, 2019 | 130 | 2019 |
An analysis of how training data complexity affects the nearest neighbor classifiers JS Sánchez, RA Mollineda, JM Sotoca Pattern Analysis and Applications 10, 189-201, 2007 | 123 | 2007 |
High training set size reduction by space partitioning and prototype abstraction JS Sánchez Pattern Recognition 37 (7), 1561-1564, 2004 | 118 | 2004 |
An insight into the experimental design for credit risk and corporate bankruptcy prediction systems V García, AI Marqués, JS Sánchez Journal of Intelligent Information Systems 44 (1), 159-189, 2015 | 114 | 2015 |
Nearest neighbour editing and condensing tools–synergy exploitation BV Dasarathy, JS Sánchez, S Townsend Pattern Analysis & Applications 3, 19-30, 2000 | 111 | 2000 |