M. J. D. Jesús

María José del Jesús, Francisco Herrera, Cristóbal J. Carmona, 2011, 2011 IEEE 5th International Workshop on Genetic and Evolutionary Fuzzy Systems (GEFS).

An overview on subgroup discovery: foundations and applications

María José del Jesús, Francisco Herrera, Cristóbal J. Carmona, 2011, Knowledge and Information Systems.

NMEEF-SD: Non-dominated Multiobjective Evolutionary Algorithm for Extracting Fuzzy Rules in Subgroup Discovery

María José del Jesús, Francisco Herrera, Cristóbal J. Carmona, 2010, IEEE Transactions on Fuzzy Systems.

An analysis of evolutionary algorithms with different types of fuzzy rules in subgroup discovery

María José del Jesús, Francisco Herrera, Cristóbal J. Carmona, 2009, 2009 IEEE International Conference on Fuzzy Systems.

Non-dominated Multi-objective Evolutionary Algorithm Based on Fuzzy Rules Extraction for Subgroup Discovery

María José del Jesús, Francisco Herrera, Cristóbal J. Carmona, 2009, HAIS.

Evolutionary algorithms for subgroup discovery in e-learning: A practical application using Moodle data

María José del Jesús, Francisco Herrera, Sebastián Ventura, 2009, Expert Syst. Appl..

Subgroup Discovery with Linguistic Rules

María José del Jesús, Francisco Herrera, Pedro González, 2008, Fuzzy Sets and Their Extensions: Representation, Aggregation and Models.

Genetic tuning of fuzzy rule deep structures preserving interpretability and its interaction with fuzzy rule set reduction

María José del Jesús, Francisco Herrera, Jorge Casillas, 2005, IEEE Transactions on Fuzzy Systems.

Evolutionary Induction of Descriptive Rules in a Market Problem

María José del Jesús, Francisco Herrera, Pedro González, 2005, Intelligent Data Mining.

Some relationships between fuzzy and random set-based classifiers and models

María José del Jesús, Jorge Casillas, Oscar Cordón, 2002, Int. J. Approx. Reason..

Different Proposals to Improve the Accuracy of Fuzzy Linguistic Modeling

Francisco Herrera, Oscar Cordón, María José del Jesus, 2000 .

EvoAAA: An evolutionary methodology for automated neural autoencoder architecture search

Antonio J. Rivera, María José del Jesus, Francisco Charte, 2020, Integr. Comput. Aided Eng..

Multilabel Classification

Francisco Charte, Antonio J. Rivera, María José del Jesús, 2016, Springer International Publishing.

CO ^2 RBFN-CS: First Approach Introducing Cost-Sensitivity in the Cooperative-Competitive RBFN Design

Francisco Charte, Antonio J. Rivera, María José del Jesús, 2015, IWANN.

A first analysis of the effect of local and global optimization weights methods in the cooperative-competitive design of RBFN for imbalanced environments

Antonio J. Rivera, María José del Jesús, M. Dolores Pérez-Godoy, 2013, The 2013 International Joint Conference on Neural Networks (IJCNN).

Analysis of an evolutionary RBFN design algorithm, CO2RBFN, for imbalanced data sets

María José del Jesus, Alberto Fernández, M. D. Pérez-Godoy, 2010, Pattern Recognit. Lett..

A fuzzy genetic programming-based algorithm for subgroup discovery and the application to one problem of pathogenesis of acute sore throat conditions in humans

María José del Jesús, David A. Elizondo, Cristóbal J. Carmona, 2015, Inf. Sci..

Niching genetic feature selection algorithms applied to the design of fuzzy rule-based classification systems

María José del Jesús, Francisco Herrera, Manuel Chica, 2007, 2007 IEEE International Fuzzy Systems Conference.

A hierarchical genetic fuzzy system based on genetic programming for addressing classification with highly imbalanced and borderline data-sets

María José del Jesús, Francisco Herrera, Alberto Fernández, 2013, Knowl. Based Syst..

Hierarchical fuzzy rule based classification systems with genetic rule selection for imbalanced data-sets

María José del Jesús, Francisco Herrera, Alberto Fernández, 2009, Int. J. Approx. Reason..

Multi-class Imbalanced Data-Sets with Linguistic Fuzzy Rule Based Classification Systems Based on Pairwise Learning

María José del Jesús, Francisco Herrera, Alberto Fernández, 2010, IPMU.

A proposal on reasoning methods in fuzzy rule-based classification systems

María José del Jesús, Francisco Herrera, Oscar Cordón, 1999, Int. J. Approx. Reason..

Genetic learning of fuzzy rule-based classification systems cooperating with fuzzy reasoning methods

María José del Jesús, Francisco Herrera, Oscar Cordón, 1998, Int. J. Intell. Syst..

Genetic feature selection in a fuzzy rule-based classification system learning process for high-dimensional problems

María José del Jesús, Francisco Herrera, Jorge Casillas, 2001, Inf. Sci..

Revisiting Evolutionary Fuzzy Systems: Taxonomy, applications, new trends and challenges

María José del Jesús, Francisco Herrera, Alberto Fernández, 2015, Knowl. Based Syst..

Evolutionary approaches to the learning of fuzzy rule-based classification systems

Oscar Cordón, Francisco Herrera, M. J. del Jesus, 1999 .

Analysing the classification of imbalanced data-sets with multiple classes: Binarization techniques and ad-hoc approaches

Mikel Galar, María José del Jesus, Francisco Herrera, 2013, Knowl. Based Syst..

CO2RBFN: an evolutionary cooperative–competitive RBFN design algorithm for classification problems

Antonio J. Rivera, María José del Jesús, M. Dolores Pérez-Godoy, 2010, Soft Comput..

GP-COACH: Genetic Programming-based learning of COmpact and ACcurate fuzzy rule-based classification systems for High-dimensional problems

Antonio J. Rivera, María José del Jesús, Francisco Herrera, 2010, Inf. Sci..

On the 2-tuples based genetic tuning performance for fuzzy rule based classification systems in imbalanced data-sets

María José del Jesús, Francisco Herrera, Alberto Fernández, 2010, Inf. Sci..

MOGUL: A methodology to obtain genetic fuzzy rule-based systems under the iterative rule learning approach

María José del Jesús, Francisco Herrera, Oscar Cordón, 1999, Int. J. Intell. Syst..

MEFASD-BD: Multi-objective evolutionary fuzzy algorithm for subgroup discovery in big data environments - A MapReduce solution

Antonio J. Rivera, M. Dolores Pérez-Godoy, Cristóbal J. Carmona, 2017, Knowl. Based Syst..

On the influence of an adaptive inference system in fuzzy rule based classification systems for imbalanced data-sets

María José del Jesús, Francisco Herrera, Alberto Fernández, 2009, Expert Syst. Appl..

A study of the behaviour of linguistic fuzzy rule based classification systems in the framework of imbalanced data-sets

María José del Jesús, Francisco Herrera, Salvador García, 2008, Fuzzy Sets Syst..

KEEL 3.0: An Open Source Software for Multi-Stage Analysis in Data Mining

María José del Jesús, Francisco Herrera, Jesús Alcalá-Fdez, 2017, Int. J. Comput. Intell. Syst..

Characterization of Concentrating Photovoltaic modules by cooperative competitive Radial Basis Function Networks

Antonio J. Rivera, María José del Jesús, Jorge Aguilera, 2013, Expert Syst. Appl..

An analysis on the use of autoencoders for representation learning: fundamentals, learning task case studies, explainability and challenges

Francisco Herrera, David Charte, Francisco Charte, 2020, Neurocomputing.

A Big Data Approach for the Extraction of Fuzzy Emerging Patterns

María José del Jesús, Ángel Miguel García-Vico, Pedro González, 2019, Cognitive Computation.

Short, medium and long term forecasting of time series using the L-Co-R algorithm

María José del Jesús, Maribel García Arenas, Víctor Manuel Rivas Santos, 2014, Neurocomputing.

Coevolution of lags and RBFNs for time series forecasting: L-Co-R algorithm

María José del Jesús, Maribel García Arenas, Víctor Manuel Rivas Santos, 2011, Soft Computing.

Analysing the Hierarchical Fuzzy Rule Based Classification Systems with genetic rule selection

María José del Jesús, Francisco Herrera, Alberto Fernández, 2010, 2010 4th International Workshop on Genetic and Evolutionary Fuzzy Systems (GEFS).

Designing Radial Basis Function Neural Networks with Meta-Evolutionary Algorithms: The Effect of Chromosome Codification

María José del Jesús, Juan Julián Merelo Guervós, Víctor Manuel Rivas Santos, 2009, IWANN.

Automatic Neural Net Design by Means of a Symbiotic Co-evolutionary Algorithm

María José del Jesús, Víctor Manuel Rivas Santos, Elisabet Parras-Gutierrez, 2008, HAIS.

A Short Study on the Use of Genetic 2-Tuples Tuning for Fuzzy Rule Based Classification Systems in Imbalanced Data-Sets

María José del Jesús, Francisco Herrera, Alberto Fernández, 2008, 2008 Eighth International Conference on Hybrid Intelligent Systems.

A Symbiotic CHC Co-evolutionary Algorithm for Automatic RBF Neural Networks Design

María José del Jesús, Juan Julián Merelo Guervós, Víctor Manuel Rivas Santos, 2008, DCAI.

Parallelizing the Design of Radial Basis Function Neural Networks by Means of Evolutionary Meta-algorithms

María José del Jesús, Juan Julián Merelo Guervós, Pedro A. Castillo, 2009, IWANN.

A distributed evolutionary fuzzy system-based method for the fusion of descriptive emerging patterns in data streams

C. J. Carmona, M. J. del Jesus, M. J. D. Jesús, 2022, Inf. Fusion.

A cellular-based evolutionary approach for the extraction of emerging patterns in massive data streams

Cristóbal J. Carmona, María José del Jesus, Ángel Miguel García-Vico, 2021, Expert Syst. Appl..

FEPDS: A Proposal for the Extraction of Fuzzy Emerging Patterns in Data Streams

Ángel Miguel García-Vico, Cristóbal J. Carmona, Huseyin Seker, 2020, IEEE Transactions on Fuzzy Systems.

A unifying analysis for the supervised descriptive rule discovery via the weighted relative accuracy

María José del Jesús, Francisco Herrera, Cristóbal J. Carmona, 2018, Knowl. Based Syst..

Multiobjective Genetic Algorithm for Extracting Subgroup Discovery Fuzzy Rules

María José del Jesús, Francisco Herrera, Pedro González, 2007, 2007 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making.

Multiobjective Evolutionary Induction of Subgroup Discovery Fuzzy Rules: A Case Study in Marketing

María José del Jesús, Francisco Herrera, Francisco José Berlanga, 2006, ICDM.

Big Data with Cloud Computing: an insight on the computing environment, MapReduce, and programming frameworks

María José del Jesús, Francisco Herrera, Alberto Fernández, 2014, WIREs Data Mining Knowl. Discov..

A novel genetic cooperative-competitive fuzzy rule based learning method using genetic programming for high dimensional problems

María José del Jesús, Francisco Herrera, Francisco José Berlanga, 2008, 2008 3rd International Workshop on Genetic and Evolving Systems.

An analysis on the use of pre-processing methods in evolutionary fuzzy systems for subgroup discovery

María José del Jesús, Cristóbal J. Carmona, Julián Luengo, 2012, Expert Syst. Appl..

Evolutionary Fuzzy Systems for Explainable Artificial Intelligence: Why, When, What for, and Where to?

María José del Jesús, Francisco Herrera, Oscar Cordón, 2019, IEEE Computational Intelligence Magazine.

Alternative OVA Proposals for Cooperative Competitive RBFN Design in Classification Tasks

Francisco Charte, Antonio J. Rivera, María José del Jesús, 2013, IWANN.

Multi-label Testing for CO2RBFN: A First Approach to the Problem Transformation Methodology for Multi-label Classification

Francisco Charte, Antonio J. Rivera, María José del Jesús, 2011, IWANN.

A study on the medium-term forecasting using exogenous variable selection of the extra-virgin olive oil with soft computing methods

M. Dolores Pérez-Godoy, Antonio J. Rivera, Pedro Pérez-Recuerda, 2011, Applied Intelligence.

Intelligent Systems in Long-Term Forecasting of the Extra-Virgin Olive Oil Price in the Spanish Market

Antonio J. Rivera, María José del Jesús, M. Dolores Pérez-Godoy, 2010, IEA/AIE.

CO2RBFN for short-term forecasting of the extra virgin olive oil price in the Spanish market

Antonio J. Rivera, María José del Jesús, M. Dolores Pérez-Godoy, 2010, Int. J. Hybrid Intell. Syst..

A Preliminar Analysis of CO2RBFN in Imbalanced Problems

Antonio J. Rivera, María José del Jesús, Francisco Herrera, 2009, IWANN.

CoEvRBFN: An Approach to Solving the Classification Problem with a Hybrid Cooperative-Coevolutive Algorithm

Ignacio Rojas, Antonio J. Rivera, María José del Jesús, 2007, IWANN.

A new hybrid methodology for cooperative-coevolutionary optimization of radial basis function networks

Ignacio Rojas, Antonio J. Rivera, Julio Ortega Lopera, 2007, Soft Comput..

A differential evolution proposal for estimating the maximum power delivered by CPV modules under real outdoor conditions

Antonio J. Rivera, María José del Jesús, Jorge Aguilera, 2015, Expert Syst. Appl..

Mining Context-Aware Association Rules Using Grammar-Based Genetic Programming

María José del Jesús, Mykola Pechenizkiy, Sebastián Ventura, 2018, IEEE Transactions on Cybernetics.

On the discovery of association rules by means of evolutionary algorithms

María José del Jesús, Jose Miguel Puerta, José A. Gámez, 2011, WIREs Data Mining Knowl. Discov..

Evolutionary Fuzzy Rule Induction Process for Subgroup Discovery: A Case Study in Marketing

María José del Jesús, Francisco Herrera, Pedro González, 2007, IEEE Transactions on Fuzzy Systems.

Subgroup Discovery on Multiple Instance Data

María José del Jesús, Sebastián Ventura, Cristóbal J. Carmona, 2019, Int. J. Comput. Intell. Syst..

LI-MLC: A Label Inference Methodology for Addressing High Dimensionality in the Label Space for Multilabel Classification

Francisco Charte, Antonio J. Rivera, María José del Jesús, 2014, IEEE Transactions on Neural Networks and Learning Systems.

Dealing with Difficult Minority Labels in Imbalanced Mutilabel Data Sets

Francisco Charte, Antonio J. Rivera, María José del Jesús, 2017, Neurocomputing.

On the Impact of Imbalanced Data in Convolutional Neural Networks Performance

Francisco Charte, Antonio J. Rivera, María José del Jesús, 2017, HAIS.

MLSMOTE: Approaching imbalanced multilabel learning through synthetic instance generation

Francisco Charte, Antonio J. Rivera, María José del Jesús, 2015, Knowl. Based Syst..

Addressing imbalance in multilabel classification: Measures and random resampling algorithms

Francisco Charte, Antonio J. Rivera, Francisco Herrera, 2015, Neurocomputing.

Resampling Multilabel Datasets by Decoupling Highly Imbalanced Labels

Francisco Charte, Antonio J. Rivera, María José del Jesús, 2015, HAIS.

Concurrence among Imbalanced Labels and Its Influence on Multilabel Resampling Algorithms

Francisco Charte, Antonio J. Rivera, María José del Jesús, 2014, HAIS.

A First Approach to Deal with Imbalance in Multi-label Datasets

A. J. Rivera, F. Herrera, M. J. D. Jesús, 2013, HAIS.

Improving the Performance of Fuzzy Rule Based Classification Systems for Highly Imbalanced Data-Sets Using an Evolutionary Adaptive Inference System

María José del Jesús, Francisco Herrera, Alberto Fernández, 2009, IWANN.

An Analysis of the Rule Weights and Fuzzy Reasoning Methods for Linguistic Rule Based Classification Systems Applied to Problems with Highly Imbalanced Data Sets

María José del Jesús, Francisco Herrera, Salvador García, 2007, WILF.

A Study on the Use of the Fuzzy Reasoning Method Based on the Winning Rule vs. Voting Procedure for Classification with Imbalanced Data Sets

María José del Jesús, Francisco Herrera, Salvador García, 2007, IWANN.

Cost Sensitive and Preprocessing for Classification with Imbalanced Data-sets: Similar Behaviour and Potential Hybridizations

María José del Jesús, Francisco Herrera, Alberto Fernández, 2012, ICPRAM.

Genetic Cooperative-Competitive Fuzzy Rule Based Learning Method using Genetic Programming for Highly Imbalanced Data-Sets

María José del Jesús, Francisco Herrera, Alberto Fernández, 2009, IFSA/EUSFLAT Conf..

AEkNN: An AutoEncoder kNN-based classifier with built-in dimensionality reduction pdf

Francisco Charte, Antonio J. Rivera, María José del Jesús, 2018, Int. J. Comput. Intell. Syst..

A Genetic-Programming-Based Approach for the Learning of Compact Fuzzy Rule-Based Classification Systems

María José del Jesús, Francisco Herrera, María José Gacto, 2006, ICAISC.

Induction of fuzzy-rule-based classifiers with evolutionary boosting algorithms

María José del Jesús, Luciano Sánchez, Frank Hoffmann, 2004, IEEE Transactions on Fuzzy Systems.

Co-evolutionary Algorithm for RBF by Self-Organizing Population of Neurons

Ignacio Rojas, Antonio J. Rivera, María José del Jesús, 2003, IWANN.

R Ultimate Multilabel Dataset Repository

Francisco Charte, Antonio J. Rivera, María José del Jesús, 2016, HAIS.

Addressing Overlapping in Classification with Imbalanced Datasets: A First Multi-objective Approach for Feature and Instance Selection

María José del Jesús, Francisco Herrera, Alberto Fernández, 2015, IDEAL.

An evolutionary paradigm for designing fuzzy rule-based systems from examples

Oscar Cordón, Manuel Lozano, Francisco Herrera, 1997 .

A Pareto-based Ensemble with Feature and Instance Selection for Learning from Multi-Class Imbalanced Datasets

María José del Jesús, Francisco Herrera, Cristóbal J. Carmona, 2017, Int. J. Neural Syst..

MLeNN: A First Approach to Heuristic Multilabel Undersampling

Francisco Charte, Antonio J. Rivera, María José del Jesús, 2014, IDEAL.

Tips, guidelines and tools for managing multi-label datasets: the mldr.datasets R package and the Cometa data repository

Francisco Charte, Antonio J. Rivera, María José del Jesús, 2018, Neurocomputing.

A Showcase of the Use of Autoencoders in Feature Learning Applications pdf

Francisco Charte, María José del Jesús, Francisco Herrera, 2019, IWINAC.

Improving Multi-label Classifiers via Label Reduction with Association Rules

Francisco Charte, Antonio J. Rivera, María José del Jesús, 2012, HAIS.

Adaptation-Based Classifiers

Francisco Charte, Antonio J. Rivera, Francisco Herrera, 2016 .

Tackling Multilabel Imbalance through Label Decoupling and Data Resampling Hybridization

Francisco Charte, Antonio J. Rivera, María José del Jesús, 2017, Neurocomputing.

A View on Fuzzy Systems for Big Data: Progress and Opportunities

María José del Jesús, Francisco Herrera, Cristóbal J. Carmona, 2016, Int. J. Comput. Intell. Syst..

XAIRE: An ensemble-based methodology for determining the relative importance of variables in regression tasks. Application to a hospital emergency department

M. D. Pérez-Godoy, A. J. Rivera, D. Elizondo, 2023, Artif. Intell. Medicine.

On the Classification of Imbalanced Datasets

H. S. Sheshadri, Kok Wai Wong, C. Lee Giles, 2012 .