María José del Jesús

发表

A preliminary study on mutation operators in cooperative competitive algorithms for RBFN design

Antonio J. Rivera, María José del Jesús, M. Dolores Pérez-Godoy, 2010, The 2010 International Joint Conference on Neural Networks (IJCNN).

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..

Analysing Concentrating Photovoltaics Technology Through the Use of Emerging Pattern Mining

María José del Jesús, Jorge Aguilera, Cristóbal J. Carmona, 2016, SOCO-CISIS-ICEUTE.

EMORBFN: An Evolutionary Multiobjetive Optimization Algorithm for RBFN Design

Antonio J. Rivera, María José del Jesús, M. Dolores Pérez-Godoy, 2009, IWANN.

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.

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

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

Concurrence among Imbalanced Labels and Its Influence on Multilabel Resampling Algorithms

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

Evolutionary fuzzy rule extraction for subgroup discovery in a psychiatric emergency department

María José del Jesús, Cristóbal J. Carmona, Pedro González, 2011, Soft Comput..

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..

MLeNN: A First Approach to Heuristic Multilabel Undersampling

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

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

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

Fuzzy rules for describing subgroups from Influenza A virus using a multi-objective evolutionary algorithm

María José del Jesús, Cristóbal J. Carmona, Huseyin Seker, 2013, Appl. Soft Comput..

A Big Data Approach for the Extraction of Fuzzy Emerging Patterns

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

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..

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

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

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.

MLSMOTE: Approaching imbalanced multilabel learning through synthetic instance generation

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

Resampling Multilabel Datasets by Decoupling Highly Imbalanced Labels

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

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 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).

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..

A Performance Study of Concentrating Photovoltaic Modules Using Neural Networks: An Application with CO2RBFN

Antonio J. Rivera, María José del Jesús, Jorge Aguilera, 2012, SOCO.

Evolutionary and metaheuristics based data mining

María José del Jesús, Jose Miguel Puerta, José A. Gámez, 2009, Soft Comput..

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..

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.

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..

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.

Dealing with Difficult Minority Labels in Imbalanced Mutilabel Data Sets

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

Study of the Robustness of a Meta-Algorithm for the Estimation of Parameters in Artificial Neural Networks Design

María José del Jesús, Juan Julián Merelo Guervós, Víctor Manuel Rivas Santos, 2008, 2008 Eighth International Conference on Hybrid Intelligent Systems.

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..

MEFES: An evolutionary proposal for the detection of exceptions in subgroup discovery. An application to Concentrating Photovoltaic Technology

María José del Jesús, Jorge Aguilera, B. García-Domingo, 2013, Knowl. Based Syst..

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 Summary on the Study of the Medium-Term Forecasting of the Extra-Virgen Olive Oil Price

Antonio J. Rivera, María José del Jesús, M. Dolores Pérez-Godoy, 2011, CAEPIA.

An overview on subgroup discovery: foundations and applications

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

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 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..

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.

Improving Multi-label Classifiers via Label Reduction with Association Rules

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

Learning compact fuzzy rule-based classification systems with genetic programming

María José del Jesús, Francisco Herrera, Francisco José Berlanga, 2005, EUSFLAT Conf..

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.

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..

Techniques of Engineering Applied to a Non-structured Data Model

María José del Jesús, Pablo Guerrero, Cristóbal J. Carmona, 2008, DCAI.

Automating Autoencoder Architecture Configuration: An Evolutionary Approach

Francisco Charte, Antonio J. Rivera, María José del Jesús, 2019, IWINAC.

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.

QUINTA: A question tagging assistant to improve the answering ratio in electronic forums

Francisco Charte, Antonio J. Rivera, María José del Jesús, 2015, IEEE EUROCON 2015 - International Conference on Computer as a Tool (EUROCON).

Evolutionary Induction of Descriptive Rules in a Market Problem

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

Subgroup Discovery Applied to the e-Commerce Website OrOliveSur.com

María José del Jesús, Sergio Ramírez-Gallego, Cristóbal J. Carmona, 2012, ICEIS.

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.

Overview on evolutionary subgroup discovery: analysis of the suitability and potential of the search performed by evolutionary algorithms

María José del Jesús, Francisco Herrera, Cristóbal J. Carmona, 2014, WIREs Data Mining Knowl. Discov..

A first approach to handle fuzzy emerging patterns mining on big data problems: The EvAEFP-spark algorithm

María José del Jesús, Cristóbal J. Carmona, Ángel Miguel García-Vico, 2017, 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).

Improvement of subgroup descriptions in noisy data by detecting exceptions

María José del Jesús, Cristóbal J. Carmona, Ángel Miguel García-Vico, 2017, Progress in Artificial Intelligence.

E-tsRBF: Preliminary Results on the Simultaneous Determination of Time-Lags and Parameters of Radial Basis Function Neural Networks for Time Series Forecasting

María José del Jesús, Víctor Manuel Rivas Santos, Elisabet Parras-Gutierrez, 2009, 2009 Ninth International Conference on Intelligent Systems Design and Applications.

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.

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.

R Ultimate Multilabel Dataset Repository

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

Genetic lateral tuning for subgroup discovery with fuzzy rules using the algorithm NMEEF-SD

María José del Jesús, Cristóbal J. Carmona, María José Gacto, 2012, Int. J. Comput. Intell. Syst..

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.

KEEL: A data mining software tool integrating genetic fuzzy systems

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

KEEL: a software tool to assess evolutionary algorithms for data mining problems

María José del Jesús, Jesús Alcalá-Fdez, Francisco Herrera, 2008, Soft Comput..

A First Approach to Face Dimensionality Reduction Through Denoising Autoencoders

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

Feature Selection Algorithms Applied to Parkinson's Disease

María José del Jesús, Francisco Herrera, Jose Joaquin Aguilera, 2001, ISMDA.

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

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

Modelado cualitativo utilizando una metodología evolutiva de aprendizaje iterativo de bases de reglas difusas

María José del Jesús, Francisco Herrera, Oscar Cordón, 1998, Inteligencia Artif..

A preliminary study on missing data imputation in evolutionary fuzzy systems of subgroup discovery

María José del Jesús, Cristóbal J. Carmona, Julián Luengo, 2012, 2012 IEEE International Conference on Fuzzy Systems.

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..

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.

FuGePSD: Fuzzy Genetic Programming-based algorithm for Subgroup Discovery

María José del Jesús, Cristóbal J. Carmona, Pedro González, 2015, IFSA-EUSFLAT.

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

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

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..

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.

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..

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).

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.

Training algorithms for Radial Basis Function Networks to tackle learning processes with imbalanced data-sets

Antonio J. Rivera, María José del Jesús, M. Dolores Pérez-Godoy, 2014, Appl. Soft Comput..

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.

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

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

A Preliminar Analysis of CO2RBFN in Imbalanced Problems

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

An overview of emerging pattern mining in supervised descriptive rule discovery: taxonomy, empirical study, trends, and prospects

María José del Jesús, Cristóbal J. Carmona, Ángel Miguel García-Vico, 2018, WIREs Data Mining Knowl. Discov..

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.

Alternative OVA Proposals for Cooperative Competitive RBFN Design in Classification Tasks

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

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..

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..

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.

An Study on Data Mining Methods 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, 2008, 2008 Eighth International Conference on Hybrid Intelligent Systems.

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..

On the Impact of Dataset Complexity and Sampling Strategy in Multilabel Classifiers Performance

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

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

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

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..

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..

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.

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.

Tackling Multilabel Imbalance through Label Decoupling and Data Resampling Hybridization

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.

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 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..

Multilabel Classification

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

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.

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..

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.

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..

Analysis of the impact of using different diversity functions for the subgroup discovery algorithm NMEEF-SD

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

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.

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 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.

A Transformation Approach Towards Big Data Multilabel Decision Trees

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

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.

An evolutionary fuzzy system for the detection of exceptions in subgroup discovery

María José del Jesús, Jorge Aguilera, B. García-Domingo, 2013, 2013 Joint IFSA World Congress and NAFIPS Annual Meeting (IFSA/NAFIPS).

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..

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.

Subgroup Discovery with Linguistic Rules

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

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.

Special Issue on Genetic Fuzzy Systems and the Interpretability-Accuracy Trade-off

María José del Jesús, Francisco Herrera, Jorge Casillas, 2007, Int. J. Approx. Reason..