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Vicente García Jiménez
Vicente García Jiménez
Other namesVicente Garcia, Vicente García, Vicente Garcia Jimenez
División Multidisciplinaria de Ciudad Universitaria, Universidad Autónoma de Ciudad Juárez
Verified email at uacj.mx - Homepage
Title
Cited by
Cited by
Year
Strategies for learning in class imbalance problems
R Barandela, JS Sánchez, V García, E Rangel
Pattern Recognition 36 (3), 849-851, 2003
7132003
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
3832012
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
2472008
Index of balanced accuracy: A performance measure for skewed class distributions
V García, RA Mollineda, JS Sánchez
Iberian conference on pattern recognition and image analysis, 441-448, 2009
2002009
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
1972012
The class imbalance problem in pattern classification and learning
V García, JS Sánchez, RA Mollineda, JM Sotoca, R Alejo
II Congreso Español de Informática, 2007
185*2007
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
1652013
An empirical study of the behavior of classifiers on imbalanced and overlapped data sets
V García, J Sánchez, R Mollineda
Progress in Pattern Recognition, Image Analysis and Applications: 12th …, 2007
1412007
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
1322013
Two-level classifier ensembles for credit risk assessment
AI Marqués, V García, JS Sánchez
Expert Systems with Applications 39 (12), 10916-10922, 2012
1272012
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
1222019
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
1082015
Financial distress prediction using the hybrid associative memory with translation
L Cleofas-Sánchez, V García, AI Marqués, JS Sánchez
Applied Soft Computing 44, 144–152, 2016
812016
Theoretical Analysis of a Performance Measure for Imbalanced Data
V Garcıa, RA Mollineda, JS Sánchez
2010 20th International Conference on Pattern Recognition (ICPR), 617-620, 2010
812010
A hybrid method to face class overlap and class imbalance on neural networks and multi-class scenarios
R Alejo, RM Valdovinos, V García, JH Pacheco-Sanchez
Pattern Recognition Letters 34 (1), 380-388, 2013
752013
Combined effects of class imbalance and class overlap on instance-based classification
V García, R Alejo, JS Sánchez, JM Sotoca, RA Mollineda
Intelligent Data Engineering and Automated Learning–IDEAL 2006: 7th …, 2006
712006
Surrounding neighborhood-based SMOTE for learning from imbalanced data sets
V García, JS Sánchez, R Martín-Félez, RA Mollineda
Progress in Artificial Intelligence, 1-16, 2012
692012
Using regression models for predicting the product quality in a tubing extrusion process
V García, JS Sánchez, LA Rodríguez-Picón, LC Méndez-Gónzalez, ...
Journal of Intelligent Manufacturing 30 (6), 2535–2544, 2019
682019
Understanding the apparent superiority of over-sampling through an analysis of local information for class-imbalanced data
V García, JS Sánchez, AI Marqués, R Florencia, G Rivera
Expert Systems with Applications 15 (0), 1-19, 2020
662020
Improving the performance of the RBF neural networks trained with imbalanced samples
R Alejo, V García, JM Sotoca, RA Mollineda, JS Sánchez
Proceedings of the 9th international work conference on Artificial neural …, 2007
582007
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