José Salvador Sánchez

Filiberto Pla, José Martínez Sotoca, José Salvador Sánchez, 2007, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

A Gender Recognition Experiment on the CASIA Gait Database Dealing with Its Imbalanced Nature

José Salvador Sánchez, Raúl Martín-Félez, Ramón Alberto Mollineda, 2010, VISAPP.

On the Use of Different Classification Rules in an Editing Task

José Martínez Sotoca, Luisa Micó, José Salvador Sánchez, 2006, SSPR/SPR.

Improving the Classification Accuracy of RBF and MLP Neural Networks Trained with Imbalanced Samples

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

Human Recognition Based on Gait Poses

José Salvador Sánchez, Raúl Martín-Félez, Ramón Alberto Mollineda, 2011, IbPRIA.

Analysis of new techniques to obtain quality training sets

Roberto Alejo, José Salvador Sánchez, Ricardo Barandela, 2003, Pattern Recognit. Lett..

Complexity reduction in efficient prototype-based classification

Filiberto Pla, José Salvador Sánchez, Francesc J. Ferri, 2006, Pattern Recognit..

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..

Decision boundary preserving prototype selection for nearest neighbor classification

José Salvador Sánchez, Ricardo Barandela, Francesc J. Ferri, 2005, Int. J. Pattern Recognit. Artif. Intell..

A meta-learning framework for pattern classification by means of data complexity measures

José Martínez Sotoca, José Salvador Sánchez, Ramón Alberto Mollineda, 2006, Inteligencia Artif..

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.

Learning vector quantization with alternative distance criteria

Filiberto Pla, José Salvador Sánchez, Francesc J. Ferri, 1999, Proceedings 10th International Conference on Image Analysis and Processing.

Combining Multiple Classifiers with Dynamic Weighted Voting

Rosa Maria Valdovinos, José Salvador Sánchez, R. M. Valdovinos, 2009, HAIS.

Non Parametric Local Density-Based Clustering for Multimodal Overlapping Distributions

Filiberto Pla, José Salvador Sánchez, Damaris Pascual, 2006, IDEAL.

DBIG-US: A two-stage under-sampling algorithm to face the class imbalance problem

José Salvador Sánchez, A. Guzmán-Ponce, R. M. Valdovinos, 2020, Expert Syst. Appl..

On-Line Classification of Data Streams with Missing Values Based on Reinforcement Learning

José Salvador Sánchez, V. Javier Traver, Mónica Millán-Giraldo, 2011, IbPRIA.

Special Issue on “ Pattern Recognition for Autonomous Manipulation in Robotic Systems”

José Salvador Sánchez, Pedro J. Sanz, Raul Marin, 2005 .

Towards a More Realistic Appearance-Based Gait Representation for Gender Recognition

José Salvador Sánchez, Raúl Martín-Félez, Ramón Alberto Mollineda, 2010, 2010 20th International Conference on Pattern Recognition.

Theoretical Analysis of a Performance Measure for Imbalanced Data

José Salvador Sánchez, Ramón Alberto Mollineda, Vicente García, 2010, 2010 20th International Conference on Pattern Recognition.

An analysis of how training data complexity affects the nearest neighbor classifiers

José Martínez Sotoca, José Salvador Sánchez, Ramón Alberto Mollineda, 2007, Pattern Analysis and Applications.

Designing serious games for learning support in medicine studies: A specific method to elicit and formalize requirements

José Salvador Sánchez, Pedro Latorre Carmona, Ricardo Tosca, 2014, 2014 IEEE Frontiers in Education Conference (FIE) Proceedings.

Using the Dual of Proximity Graphs for Binary Decision Tree Design

Filiberto Pla, José Salvador Sánchez, M. C. Herrero, 2000, SSPR/SPR.

On the Use of Labelled and Unlabelled Data to Improve Nearest Neighbor Classification

Filiberto Pla, José Salvador Sánchez, Fernando Vázquez, 2006, Inteligencia Artif..

A Comparison of Techniques for Handling Incomplete Input Data with a Focus on Attribute Relevance Influence

José Salvador Sánchez, V. Javier Traver, Mónica Millán-Giraldo, 2010, 2010 Ninth International Conference on Machine Learning and Applications.

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

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

Editorial for special section at Pattern Recognition Letters - IbPRIA 2019

Hugo Proença, José Salvador Sánchez, Manuel J. Marín-Jiménez, 2020, Pattern Recognit. Lett..

High training set size reduction by space partitioning and prototype abstraction

José Salvador Sánchez, J. S. Sánchez, J. S. Sánchez, 2004, Pattern Recognit..

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

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

Attribute relevance in multiclass data sets using the naive Bayes rule

Filiberto Pla, José Martínez Sotoca, José Salvador Sánchez, 2004, ICPR 2004.

Data Characterization for Effective Prototype Selection

José Martínez Sotoca, José Salvador Sánchez, Ramón Alberto Mollineda, 2005, IbPRIA.

Estimating Feature Weights For Distance-Based Classification

Filiberto Pla, José Martínez Sotoca, José Salvador Sánchez, 2003, PRIS.

An integral automation of industrial fruit and vegetable sorting by machine vision

Filiberto Pla, José Salvador Sánchez, José Miguel Sanchiz Martí, 2001, ETFA 2001. 8th International Conference on Emerging Technologies and Factory Automation. Proceedings (Cat. No.01TH8597).

Gender Classification from Pose-Based GEIs

José Salvador Sánchez, Raúl Martín-Félez, Ramón Alberto Mollineda, 2012, ICCVG.

Hybrid Associative Memories for Imbalanced Data Classification: An Experimental Study

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

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

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

Exploring the Performance of Resampling Strategies for the Class Imbalance Problem

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

Classification of High Dimensional and Imbalanced Hyperspectral Imagery Data

José Salvador Sánchez, Ramón Alberto Mollineda, Vicente García, 2011, IbPRIA.

The Imbalanced Training Sample Problem: Under or over Sampling?

Rosa Maria Valdovinos, José Salvador Sánchez, Ricardo Barandela, 2004, SSPR/SPR.

Mapping microarray gene expression data into dissimilarity spaces for tumor classification

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

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..

A review of data complexity measures and their applicability to pattern classification problems

José Martínez Sotoca, José Salvador Sánchez, R. A. Mollineda, 2005 .

An LVQ-based adaptive algorithm for learning from very small codebooks

José Salvador Sánchez, A. I. Marqués, J. S. Sánchez, 2006, Neurocomputing.

Reducing Training Sets by NCN-based Exploratory Procedures

Filiberto Pla, José Salvador Sánchez, María Teresa Lozano, 2003, IbPRIA.

VIDEOGAMES-BASED LEARNING IN MEDICAL STUDIES: EDUCATIONAL NEEDS AND FORMALIZATION OF TECHNICAL REQUIREMENTS

José Salvador Sánchez, Ximo Granell, Ricardo Tosca, 2014 .

Imbalanced Training Set Reduction and Feature Selection Through Genetic Optimization

José Salvador Sánchez, Ricardo Barandela, Francesc J. Ferri, 2005, CCIA.

One-Sided Prototype Selection on Class Imbalanced Dissimilarity Matrices

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

Exploring Early Classification Strategies of Streaming Data with Delayed Attributes

José Salvador Sánchez, V. Javier Traver, Mónica Millán-Giraldo, 2009, ICONIP.

IMPLEMENTATION OF THE SCIENTIFIC METHOD ROADMAP INTO THE MEDICINE DEGREE OF THE UNIVERSITAT JAUME I BY DECONSTRUCTION OF SUBJECTS

José Salvador Sánchez, Ximo Granell, Ricardo Tosca, 2015 .

A Hybrid Feature Extraction Method for Offline Handwritten Math Symbol Recognition

Rosa Maria Valdovinos, José Salvador Sánchez, José Antonio Hernández Servín, 2018, CIARP.

On the equivalency between decision tree classifiers and the nearest neighbour rule

Filiberto Pla, José Salvador Sánchez, Francesc J. Ferri, 1997, Inteligencia Artif..

FIRST RESULTS OF IMPLEMENTING A PROJECT-BASED TEACHING APPROACH IN THE INTEGRATION OF THE SCIENTIFIC METHOD ROADMAP INTO THE MEDICINE DEGREE AT THE UNIVERSITAT JAUME I

José Salvador Sánchez, Ximo Granell, Ricardo Tosca, 2016 .

Online reconstruction-free single-pixel image classification

Enrique Tajahuerce, José Salvador Sánchez, V. Javier Traver, 2019, Image Vis. Comput..

Strategies for learning in class imbalance problems

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

Editing Prototypes in the Finite Sample Size Case Using Alternative Neighbourhoods

Filiberto Pla, José Salvador Sánchez, Francesc J. Ferri, 1998, SSPR/SPR.

Clustering Based on Compressed Data for Categorical and Mixed Attributes

Eréndira Rendón Lara, José Salvador Sánchez, 2006, SSPR/SPR.

Performance evaluation of prototype selection algorithms for nearest neighbor classification

Roberto Alejo, José Salvador Sánchez, Ricardo Barandela, 2001, Proceedings XIV Brazilian Symposium on Computer Graphics and Image Processing.

Improving Risk Predictions by Preprocessing Imbalanced Credit Data

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

Two-level classifier ensembles for credit risk assessment

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

A New Under-Sampling Method to Face Class Overlap and Imbalance

José Raymundo Marcial-Romero, José Salvador Sánchez, R. M. Valdovinos, 2020, Applied Sciences.

A Voronoi-diagram-based approach to oblique decision tree induction

Filiberto Pla, José Salvador Sánchez, Francesc J. Ferri, 1998, Proceedings. Fourteenth International Conference on Pattern Recognition (Cat. No.98EX170).

A comparative study of simple online learning strategies for streaming data

José Salvador Sánchez, M. Millan-Giraldo, M. Millán-Giraldo, 2008 .

Associative learning on imbalanced environments: An empirical study

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

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

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

New Applications of Ensembles of Classifiers

Rosa Maria Valdovinos, José Salvador Sánchez, Ricardo Barandela, 2003, Pattern Analysis & Applications.

Influence of Resampling and Weighting on Diversity and Accuracy of Classifier Ensembles

Eduardo Gasca, Rosa Maria Valdovinos, José Salvador Sánchez, 2007, IbPRIA.

Learning from Imbalanced Sets through Resampling and Weighting

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

Experimental study on prototype optimisation algorithms for prototype-based classification in vector spaces

Filiberto Pla, José Martínez Sotoca, Robert P. W. Duin, 2006, Pattern Recognit..

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

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

Prototype selection for the nearest neighbour rule through proximity graphs

Filiberto Pla, José Salvador Sánchez, Francesc J. Ferri, 1997, Pattern Recognit. Lett..

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..

Eliminating redundancy and irrelevance using a new MLP-based feature selection method

Eduardo Gasca, José Salvador Sánchez, R. Alonso, 2006, Pattern Recognit..

Enhanced Neighbourhood Specifications for Pattern Classification

José Salvador Sánchez, A. I. Marqués, J. S. Sánchez, 2003 .

When Overlapping Unexpectedly Alters the Class Imbalance Effects

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

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

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

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.

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

A Stochastic Approach to Wilson's Editing Algorithm

Filiberto Pla, José Salvador Sánchez, Fernando Vázquez, 2005, IbPRIA.

Using Proximity and Spatial Homogeneity in Neighbourhood-Based Classifiers

Filiberto Pla, José Salvador Sánchez, Francesc J. Ferri, 1997, ICIAP.

Empirical Study of the Associative Approach in the Context of Classification Problems

Rosa Maria Valdovinos, Héctor M. Pérez Meana, José Salvador Sánchez, 2019, Computación y Sistemas.

Efficient nearest neighbor classification with data reduction and fast search algorithms

Filiberto Pla, José Martínez Sotoca, José Salvador Sánchez, 2004, 2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583).

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

José Salvador Sánchez, Vicente García, A. I. Marqués, 2014, Journal of Intelligent Information Systems.

Attribute relevance in multiclass data sets using the naive Bayes rule

Filiberto Pla, José Martínez Sotoca, José Salvador Sánchez, 2004, Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004..

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 Density-based Hierarchical Clustering Algorithm for Highly Overlapped Distributions with Noisy Points

Filiberto Pla, José Salvador Sánchez, Damaris Pascual, 2010, CCIA.

Class-dependant resampling for medical applications

Rosa Maria Valdovinos, José Salvador Sánchez, 2005, Fourth International Conference on Machine Learning and Applications (ICMLA'05).

Exploring Synergetic Effects of Dimensionality Reduction and Resampling Tools on Hyperspectral Imagery Data Classification

José Salvador Sánchez, Ramón Alberto Mollineda, Vicente García, 2011, MLDM.

Cluster Stability Assessment Based on Theoretic Information Measures

Filiberto Pla, José Salvador Sánchez, Damaris Pascual, 2008, CIARP.

Robert P. W. Duin, José Salvador Sánchez, Mónica Millán-Giraldo, 2010, 2010 2nd International Workshop on Cognitive Information Processing.

Financial distress prediction using the hybrid associative memory with translation