V. García

发表

The class imbalance problem in pattern classiﬁcation and learning

R. A. Mollineda, J. Sotoca, V. García, 2009 .

Feature dimensionality vs. Distribution of sample types: a preliminary study on gene-expression microarrays

V. García, J. S. Sánchez, 2018 .

Deep transfer learning for the recognition of types of face masks as a core measure to prevent the transmission of COVID-19

V. García, J. S. Sánchez, G. Rivera, 2022, Applied Soft Computing.

Fuzzy-Based Time Series Forecasting and Modelling: A Bibliometric Analysis

V. García, J. S. Sánchez, L. Palomero, 2022, Applied Sciences.

An insight into the experimental design for credit risk and corporate bankruptcy prediction systems

A. I. Marqués, V. García, J. S. Sánchez, 2015, Journal of Intelligent Information Systems.

Two-level classifier ensembles for credit risk assessment

José Salvador Sánchez, Vicente García, A. I. Marqués, 2012, Expert Syst. Appl..

When Overlapping Unexpectedly Alters the Class Imbalance Effects

José Martínez Sotoca, Roberto Alejo, José Salvador Sánchez, 2007, IbPRIA.

Exploring the synergetic effects of sample types on the performance of ensembles for credit risk and corporate bankruptcy prediction

Vicente García, A. I. Marqués, J. Salvador Sánchez, 2019, Inf. Fusion.

Gene selection and disease prediction from gene expression data using a two-stage hetero-associative memory

V. García, J. S. Sánchez, Laura Cleofas-Sánchez, 2019, Progress in Artificial Intelligence.

Mapping microarray gene expression data into dissimilarity spaces for tumor classification

José Salvador Sánchez, Vicente García, V. García, 2015, Inf. Sci..

An Insight on the 'Large G, Small n' Problem in Gene-Expression Microarray Classification

José Salvador Sánchez, Humberto de Jesús Ochoa Domínguez, Francisco López-Orozco, 2017, IbPRIA.

Financial distress prediction using the hybrid associative memory with translation

José Salvador Sánchez, Vicente García, A. I. Marqués, 2016, Appl. Soft Comput..

Learning from Imbalanced Sets through Resampling and Weighting

José Salvador Sánchez, Ricardo Barandela, Francesc J. Ferri, 2003, IbPRIA.

Instance Selection for the Nearest Neighbor Classifier: Connecting the Performance to the Underlying Data Structure

Carlos Alberto Ochoa Ortíz Zezzatti, Vicente García, Josep Salvador Sánchez, 2019, IbPRIA.

On the suitability of resampling techniques for the class imbalance problem in credit scoring

José Salvador Sánchez, A. I. Marqués, Vicente García, 2013, J. Oper. Res. Soc..

Improving Risk Predictions by Preprocessing Imbalanced Credit Data

José Salvador Sánchez, A. I. Marqués, Vicente García, 2012, ICONIP.

Using regression models for predicting the product quality in a tubing extrusion process

Luis Alberto Rodríguez-Picón, Luis Carlos Méndez González, Humberto de Jesús Ochoa Domínguez, 2018, Journal of Intelligent Manufacturing.

On the effectiveness of preprocessing methods when dealing with different levels of class imbalance

José Salvador Sánchez, Ramón Alberto Mollineda, Vicente García, 2012, Knowl. Based Syst..

A bias correction function for classification performance assessment in two-class imbalanced problems

José Salvador Sánchez, Ramón Alberto Mollineda, Vicente García, 2014, Knowl. Based Syst..

An Empirical Study of the Behavior of Classifiers on Imbalanced and Overlapped Data Sets

José Salvador Sánchez, Ramón Alberto Mollineda, Vicente García, 2007, CIARP.

On the k-NN performance in a challenging scenario of imbalance and overlapping

José Salvador Sánchez, Ramón Alberto Mollineda, Vicente García, 2008, Pattern Analysis and Applications.

On the use of data filtering techniques for credit risk prediction with instance-based models

José Salvador Sánchez, Vicente García, A. I. Marqués, 2012, Expert Syst. Appl..

Vicente García, A. I. Marqués, J. Salvador Sánchez, 2017, Computational Economics.

A literature review on the application of evolutionary computing to credit scoring

José Salvador Sánchez, Vicente García, A. I. Marqués, 2013, J. Oper. Res. Soc..

Ranking-based MCDM models in financial management applications: analysis and emerging challenges

A. I. Marqués, V. García, J. S. Sánchez, 2020, Progress in Artificial Intelligence.

Surrounding neighborhood-based SMOTE for learning from imbalanced data sets

José Salvador Sánchez, Raúl Martín-Félez, Ramón Alberto Mollineda, 2012, Progress in Artificial Intelligence.

A. I. Marqués, V. García, J. S. Sánchez, 2017, Computational Economics.

Combined Effects of Class Imbalance and Class Overlap on Instance-Based Classification

José Martínez Sotoca, Roberto Alejo, José Salvador Sánchez, 2006, IDEAL.

Making Accurate Credit Risk Predictions with Cost-Sensitive MLP Neural Networks

José Salvador Sánchez, Vicente García, A. I. Marqués, 2013 .

Improving the Performance of the RBF Neural Networks Trained with Imbalanced Samples

José Martínez Sotoca, Roberto Alejo, José Salvador Sánchez, 2007, IWANN.

Exploring the behaviour of base classifiers in credit scoring ensembles

A. I. Marqués, J. S. Sánchez, V. García, 2012, Expert Syst. Appl..

One-Sided Prototype Selection on Class Imbalanced Dissimilarity Matrices

José Salvador Sánchez, Mónica Millán-Giraldo, Vicente García, 2012, SSPR/SPR.

Index of Balanced Accuracy: A Performance Measure for Skewed Class Distributions

José Salvador Sánchez, Ramón Alberto Mollineda, Vicente García, 2009, IbPRIA.

Surrounding neighborhood-based SMOTE for learning from imbalanced data sets

R. A. Mollineda, V. García, R. Martín-Félez, 2012, Progress in Artificial Intelligence.

Exploring the Performance of Resampling Strategies for the Class Imbalance Problem

José Salvador Sánchez, Ramón Alberto Mollineda, Vicente García, 2010, IEA/AIE.

Use of Ensemble Based on GA for Imbalance Problem

Roberto Alejo, Rosa Maria Valdovinos, Vicente García, 2009, ISNN.

On the use of surrounding neighbors for synthetic over-sampling of the minority class

José Salvador Sánchez, Vicente García, R. A. Mollineda, 2008 .

An Efficient Over-sampling Approach Based on Mean Square Error Back-propagation for Dealing with the Multi-class Imbalance Problem

V. García, R. Alejo, J. Pacheco-Sánchez, 2015, Neural Processing Letters.

A hybrid method to face class overlap and class imbalance on neural networks and multi-class scenarios

Roberto Alejo, J. Horacio Pacheco-Sánchez, Rosa Maria Valdovinos, 2013, Pattern Recognit. Lett..

Synergetic Application of Multi-Criteria Decision-Making Models to Credit Granting Decision Problems

A. I. Marqués, Vicente García, J. Salvador Sánchez, 2019, Applied Sciences.

Hybrid Associative Memories for Imbalanced Data Classification: An Experimental Study

R. RosaM.Valdovinos, José Salvador Sánchez, Oscar Camacho Nieto, 2013, MCPR.

Understanding the apparent superiority of over-sampling through an analysis of local information for class-imbalanced data

Rogelio Florencia Juárez, A. I. Marqués, Vicente García, 2020, Expert Syst. Appl..

Instance Selection Methods and Resampling Techniques for Dissimilarity Representation with Imbalanced Data Sets

José Salvador Sánchez, Vicente García, M. Millán-Giraldo, 2013 .

Prototype Selection in Imbalanced Data for Dissimilarity Representation - A Preliminary Study

José Salvador Sánchez, Mónica Millán-Giraldo, Vicente García, 2012, ICPRAM.

Strategies for learning in class imbalance problems

José Salvador Sánchez, Ricardo Barandela, Vicente García, 2003, Pattern Recognit..

José Salvador Sánchez, Humberto de Jesús Ochoa Domínguez, Vicente García, 2015, IbPRIA.

Strategies for learning in class imbalance problems

R. Barandelaa, E. Rangela, R. Barandela, 2003, Pattern Recognit..

A regression model based on the nearest centroid neighborhood

A. I. Marqués, V. García, R. Martínez-Peláez, 2018, Pattern Analysis and Applications.

Addressing the Links Between Dimensionality and Data Characteristics in Gene-Expression Microarrays

Vicente García, J. Salvador Sánchez, V. García, 2018, LOPAL '18.

Associative learning on imbalanced environments: An empirical study

R. RosaM.Valdovinos, José Salvador Sánchez, Vicente García, 2016, Expert Syst. Appl..

Cost-Sensitive Neural Networks and Editing Techniques for Imbalance Problems

José Martínez Sotoca, Roberto Alejo, Rosa Maria Valdovinos, 2010, MCPR.

Ranking-based MCDM models in financial management applications: analysis and emerging challenges

A. I. Marqués, Vicente García, J. Salvador Sánchez, 2020, Progress in Artificial Intelligence.

Model Selection for Financial Distress Prediction by Aggregating TOPSIS and PROMETHEE Rankings

José Salvador Sánchez, A. I. Marqués, Vicente García, 2016, HAIS.

Assessment of Financial Risk Prediction Models with Multi-criteria Decision Making Methods

José Salvador Sánchez, Vicente García, A. I. Marqués, 2012, ICONIP.

Identifying Suggestions in Airline-User Tweets Using Natural Language Processing and Machine Learning

Karla Olmos-Sánchez, Jorge Rodas-Osollo, Vicente García, 2021 .