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Vicente García Jiménez
Vicente García Jiménez
Otros nombresVicente Garcia, Vicente García, Vicente Garcia Jimenez
División Multidisciplinaria de Ciudad Universitaria, Universidad Autónoma de Ciudad Juárez
Dirección de correo verificada de uacj.mx - Página principal
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Strategies for learning in class imbalance problems
R Barandela, JS Sánchez, V García, E Rangel
Pattern Recognition 36 (3), 849-851, 2003
7662003
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
4462012
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
2822008
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
2612009
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
2142012
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
196*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
1892013
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
1672013
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
1672007
Two-level classifier ensembles for credit risk assessment
AI Marqués, V García, JS Sánchez
Expert Systems with Applications 39 (12), 10916-10922, 2012
1472012
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
1452019
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
1122015
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
1012020
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
992010
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
952016
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
892013
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
832019
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
772012
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
722006
Ranking-based MCDM models in financial management applications: analysis and emerging challenges
AI Marqués, V García, JS Sánchez
Progress in Artificial Intelligence 9, 171-193, 2020
682020
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