Francisco Herrera

发表

Genetic learning of accurate TS models based on local fuzzy prototyping

Francisco Herrera, Jesús Alcalá-Fdez, Rafael Alcalá, 2003, EUSFLAT Conf..

New trends in fuzzy modeling. part II: applications

Francisco Herrera, Adel M. Alimi, 2006, Soft Comput..

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..

A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithms

Francisco Herrera, Salvador García, Joaquín Derrac, 2011, Swarm Evol. Comput..

Brightness guided preprocessing for automatic cold steel weapon detection in surveillance videos with deep learning

Francisco Herrera, Alberto Castillo, Siham Tabik, 2019, Neurocomputing.

A Sequential Selection Process in Group Decision Making with a Linguistic Assessment Approach

Francisco Herrera, Enrique Herrera-Viedma, José L. Verdegay, 1995, Inf. Sci..

Ensemble-Based Classifiers

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

A Fuzzy Model to Evaluate the Suitability of Installing an ERP System

Francisco Herrera, Enrique Herrera-Viedma, Pedro J. Sánchez, 2004 .

2019 IEEE Symposium Series on Computational Intelligence

Robert Kozma, Francisco Herrera, Raymond Chiong, 2019, IEEE Computational Intelligence Magazine.

Intuitionistic Fuzzy Analytic Network Process

Francisco Herrera, Zeshui Xu, Huchang Liao, 2018, IEEE Transactions on Fuzzy Systems.

Proyecto KEEL: Desarrollo de una herramienta para el análisis e implementación de algoritmos de extracción de conocimiento evolutivos

Francisco Herrera, Jesús Alcalá-Fdez, Luciano Sánchez, 2004 .

A multi-objective evolutionary algorithm for an effective tuning of fuzzy logic controllers in heating, ventilating and air conditioning systems

Francisco Herrera, Rafael Alcalá, María José Gacto, 2012, Applied Intelligence.

Simultaneously Evolving Deep Reinforcement Learning Models using Multifactorial optimization

Francisco Herrera, Javier Del Ser, Eneko Osaba, 2020, 2020 IEEE Congress on Evolutionary Computation (CEC).

Fuzzy-rough imbalanced learning for the diagnosis of High Voltage Circuit Breaker maintenance: The SMOTE-FRST-2T algorithm

Francisco Herrera, Chris Cornelis, Rafael Bello, 2016, Eng. Appl. Artif. Intell..

EUSBoost: Enhancing ensembles for highly imbalanced data-sets by evolutionary undersampling

Francisco Herrera, Mikel Galar, Edurne Barrenechea Tartas, 2013, Pattern Recognit..

Modeling dynamics of a real-coded CHC algorithm in terms of dynamical probability distributions

Francisco Herrera, Daniel Molina, Jesús Marín, 2012, Soft Comput..

Flintstones: A Fuzzy Linguistic Decision Tools Enhancement Suite

Francisco Herrera, Luis Martínez, Rosa M. Rodríguez, 2015 .

Evolutionary selection of hyperrectangles in nested generalized exemplar learning

Francisco Herrera, Salvador García, Cristóbal J. Carmona, 2011, Appl. Soft Comput..

Tuning fuzzy logic controllers by genetic algorithms

Francisco Herrera, José L. Verdegay, Manuel Lozano, 1995, Int. J. Approx. Reason..

On a new methodology for ranking fuzzy numbers and its application to real economic data

Francisco Herrera, Antonio-Francisco Roldán-López-de-Hierro, Concepción Roldán, 2018, Fuzzy Sets Syst..

A first attempt on evolutionary prototype reduction for nearest neighbor one-class classification

Francisco Herrera, Salvador García, Bartosz Krawczyk, 2014, 2014 IEEE Congress on Evolutionary Computation (CEC).

Special Issue SOCO 2017: New trends in soft computing and its application in industrial and environmental problems

Francisco Herrera, Ajith Abraham, Hilde Pérez, 2020, Neurocomputing.

A Preliminary Study on the Use of Fuzzy Rough Set Based Feature Selection for Improving Evolutionary Instance Selection Algorithms

Francisco Herrera, Chris Cornelis, Salvador García, 2011, IWANN.

Theory and Methodology Choice functions and mechanisms for linguistic preference relations

Francisco Herrera, Enrique Herrera-Viedma, F. Herrera, 2000 .

Hybridizing genetic algorithms with sharing scheme and evolution strategies for designing approximate fuzzy rule-based systems

Francisco Herrera, Oscar Cordón, 2001, Fuzzy Sets Syst..

Handling High-Dimensional Regression Problems by Means of an Efficient Multi-Objective Evolutionary Algorithm

Francisco Herrera, Rafael Alcalá, María José Gacto, 2009, 2009 Ninth International Conference on Intelligent Systems Design and Applications.

Weighted one-class classification for different types of minority class examples in imbalanced data

Francisco Herrera, Bartosz Krawczyk, Michal Wozniak, 2014, 2014 IEEE Symposium on Computational Intelligence and Data Mining (CIDM).

Evaluating the classifier behavior with noisy data considering performance and robustness: The Equalized Loss of Accuracy measure

Francisco Herrera, Julián Luengo, José A. Sáez, 2016, Neurocomputing.

Teranga Go!: Carpooling Collaborative Consumption Community with multi-criteria hesitant fuzzy linguistic term set opinions to build confidence and trust

Francisco Herrera, Ana M. Sánchez, Rosana Montes-Soldado, 2018, Appl. Soft Comput..

A memetic algorithm using local search chaining forblack-box optimization benchmarking 2009 for noise free functions

Francisco Herrera, Daniel Molina, Manuel Lozano, 2009, GECCO '09.

A Taxonomy and Experimental Study on Prototype Generation for Nearest Neighbor Classification

Francisco Herrera, Salvador García, Joaquín Derrac, 2012, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

Consensus Based on Fuzzy Coincidence for Group Decision Making in Linguistic Setting

Francisco Herrera, Enrique Herrera-Viedma, José L. Verdegay, 1997 .

Addressing the Classification with Imbalanced Data: Open Problems and New Challenges on Class Distribution

Francisco Herrera, Salvador García, Alberto Fernández, 2011, HAIS.

A preliminary study on overlapping and data fracture in imbalanced domains by means of Genetic Programming-based feature extraction

Francisco Herrera, Jose G. Moreno-Torres, F. Herrera, 2010, 2010 10th International Conference on Intelligent Systems Design and Applications.

Hierarchical distributed genetic algorithms

Francisco Herrera, Claudio Moraga, Manuel Lozano, 1999, Int. J. Intell. Syst..

Cost-Sensitive Learning

Francisco Herrera, Mikel Galar, Salvador García, 2018 .

GENERATING FUZZY RULES FROM EXAMPLES USING GENETIC ALGORITHMS

Francisco Herrera, Manuel Lozano, José L. Verdegay, 1995 .

A three-stage evolutionary process for learning descriptive and approximate fuzzy-logic-controller knowledge bases from examples

Francisco Herrera, Oscar Cordón, F. Herrera, 1997, Int. J. Approx. Reason..

Additive consistency as a tool to solve group decision making problems

Francisco Herrera, Enrique Herrera-Viedma, Sergio Alonso, 2004 .

Advances in Artificial Intelligence

Francisco Herrera, Rosana Montes, Sergio Damas, 2018, Lecture Notes in Computer Science.

Subgroup discover in large size data sets preprocessed using stratified instance selection for increasing the presence of minority classes

Francisco Herrera, José Ramón Cano, Salvador García, 2008, Pattern Recognit. Lett..

Building fuzzy graphs: Features and taxonomy of learning for non-grid-oriented fuzzy rule-based systems

Francisco Herrera, Rafael Alcalá, Jorge Casillas, 2001, J. Intell. Fuzzy Syst..

Stratified prototype selection based on a steady-state memetic algorithm: a study of scalability

Francisco Herrera, Salvador García, Joaquín Derrac, 2010, Memetic Comput..

MRPR: A MapReduce solution for prototype reduction in big data classification

Francisco Herrera, Salvador García, Jaume Bacardit, 2015, Neurocomputing.

OWA-FRPS: A Prototype Selection Method Based on Ordered Weighted Average Fuzzy Rough Set Theory

Francisco Herrera, Chris Cornelis, Nele Verbiest, 2013, RSFDGrC.

Quality Data Processing for Deep Learning

Francisco Herrera, Francisco Herrera, 2019, COMPLEXIS.

A genetic learning of the fuzzy rule-based classification system granularity for highly imbalanced data-sets

Francisco Herrera, Alberto Fernández, Pedro Villar, 2009, 2009 IEEE International Conference on Fuzzy Systems.

A taxonomy and an empirical analysis of multiple objective ant colony optimization algorithms for the bi-criteria TSP

Francisco Herrera, Oscar Cordón, Carlos García-Martínez, 2007, Eur. J. Oper. Res..

Data Preparation Basic Models

Francisco Herrera, Salvador García, Julián Luengo, 2015 .

Real‐parameter crossover operators with multiple descendents: An experimental study

Francisco Herrera, Ana M. Sánchez, Daniel Molina, 2008, Int. J. Intell. Syst..

Rationality of induced ordered weighted operators based on the reliability of the source of information in group decision-making

Francisco Herrera, Enrique Herrera-Viedma, Francisco Chiclana, 2004, Kybernetika.

Rule Base Reduction and Genetic Tuning of Fuzzy Systems Based on the Linguistic 3-tuples Representation

Francisco Herrera, Jesús Alcalá-Fdez, Rafael Alcalá, 2006, Soft Comput..

From Big to Smart Data: Iterative ensemble filter for noise filtering in Big Data classification

Francisco Herrera, Julián Luengo, Diego García-Gil, 2019, Int. J. Intell. Syst..

Other Genetic Fuzzy Rule-Based System Paradigms

Francisco Herrera, Luis Magdalena, Oscar Cordón, 2001 .

A MapReduce Approach to Address Big Data Classification Problems Based on the Fusion of Linguistic Fuzzy Rules

Francisco Herrera, José Manuel Benítez, Victoria López, 2015, Int. J. Comput. Intell. Syst..

Heuristic Crossovers for Real-Coded Genetic Algorithms Based on Fuzzy Connectives

Francisco Herrera, Manuel Lozano, F. Herrera, 1996, PPSN.

Addressing data complexity for imbalanced data sets: analysis of SMOTE-based oversampling and evolutionary undersampling

Francisco Herrera, Salvador García, Alberto Fernández, 2011, Soft Comput..

Transformation-Based Classifiers

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

Statistical analysis of convergence performance throughout the evolutionary search: A case study with SaDE-MMTS and Sa-EPSDE-MMTS

Francisco Herrera, Salvador García, Ponnuthurai N. Suganthan, 2013, 2013 IEEE Symposium on Differential Evolution (SDE).

Introduction to KDD and Data Science

Francisco Herrera, Mikel Galar, Salvador García, 2018 .

Enhancing the classification of social media opinions by optimizing the structural information

Francisco Herrera, Sebastián Maldonado, Carla Vairetti, 2020, Future Gener. Comput. Syst..

A Compact Evolutionary Interval-Valued Fuzzy Rule-Based Classification System for the Modeling and Prediction of Real-World Financial Applications With Imbalanced Data

Francisco Herrera, Hani Hagras, Humberto Bustince, 2015, IEEE Transactions on Fuzzy Systems.

Ten Lectures on Genetic Fuzzy Systems

Francisco Herrera, Ulrich Bodenhofer, F. Herrera, 1997 .

Generating the knowledge base of a fuzzy rule-based system by the genetic learning of the data base

Francisco Herrera, Oscar Cordón, Pedro Villar, 2001, IEEE Trans. Fuzzy Syst..

Fuzzy sets and operations research: Perspectives

Francisco Herrera, José L. Verdegay, F. Herrera, 1997, Fuzzy Sets Syst..

A Multi-Objective Evolutionary Algorithm for Rule Selection and Tuning on Fuzzy Rule-Based Systems

Francisco Herrera, Jesús Alcalá-Fdez, Rafael Alcalá, 2007, 2007 IEEE International Fuzzy Systems Conference.

DNBMA: A Double Normalization-Based Multi-Aggregation Method

Francisco Herrera, Huchang Liao, Xingli Wu, 2018, IPMU.

Adaptive Genetic Algorithms Based on Fuzzy Techniques

Francisco Herrera, Manuel Lozano, F. Herrera, 2007 .

A Walk into Metaheuristics for Engineering Optimization: Principles, Methods and Recent Trends

Francisco Herrera, Ning Xiong, Daniel Molina, 2015, Int. J. Comput. Intell. Syst..

Concurrence among Imbalanced Labels and Its Influence on Multilabel Resampling Algorithms

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

Preprocessing methodology for time series: An industrial world application case study

Francisco Herrera, Julián Luengo, Salvador García, 2020, Inf. Sci..

Dynamic ensemble selection for multi-class imbalanced datasets

Francisco Herrera, Abdulrahman H. Altalhi, Salvador García, 2018, Inf. Sci..

Revisiting Data Complexity Metrics Based on Morphology for Overlap and Imbalance: Snapshot, New Overlap Number of Balls Metrics and Singular Problems Prospect pdf

Francisco Herrera, Jos'e Daniel Pascual-Triana, David Charte, 2020, ArXiv.

On the Suitability of Fuzzy Rule-Based Classification Systems with Noisy Data

Francisco Herrera, Julián Luengo, José A. Sáez, 2012, IEEE transactions on fuzzy systems.

Federated Learning and Differential Privacy: Software tools analysis, the Sherpa.ai FL framework and methodological guidelines for preserving data privacy

Francisco Herrera, Eugenio Martínez-Cámara, M. Victoria Luzón, 2020, Inf. Fusion.

Dimensionality Reduction for Imbalanced Learning

Francisco Herrera, Mikel Galar, Salvador García, 2018 .

OCAPIS: R package for Ordinal Classification and Preprocessing in Scala

Pedro Antonio Gutiérrez, Francisco Herrera, Salvador García, 2018, Progress in Artificial Intelligence.

Solving Electrical Distribution Problems Using Hybrid Evolutionary Data Analysis Techniques

Francisco Herrera, Oscar Cordón, Luciano Sánchez, 2004, Applied Intelligence.

Implementation of Unsupervised Neural Architectures [R package ruta version 1.1.0]

Francisco Herrera, David Charte, Francisco Charte, 2019 .

Preprocessing noisy imbalanced datasets using SMOTE enhanced with fuzzy rough prototype selection

Francisco Herrera, Chris Cornelis, Nele Verbiest, 2014, Appl. Soft Comput..

Sentiment Analysis based Multi-person Multi-criteria Decision Making Methodology: Using Natural Language Processing and Deep Learning for Decision Aid pdf

Francisco Herrera, Enrique Herrera-Viedma, Cristina Zuheros, 2020, ArXiv.

MA-SW-Chains: Memetic algorithm based on local search chains for large scale continuous global optimization

Francisco Herrera, Daniel Molina, Manuel Lozano, 2010, IEEE Congress on Evolutionary Computation.

MLeNN: A First Approach to Heuristic Multilabel Undersampling

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

On the use of MapReduce to build linguistic fuzzy rule based classification systems for big data

Francisco Herrera, José Manuel Benítez, Victoria López, 2014, 2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).

An Experimental Case of Study on the Behavior of Multiple Classifier Systems with Class Noise Datasets

Francisco Herrera, Mikel Galar, Julián Luengo, 2013, HAIS.

Obtaining accurate TSK Fuzzy Rule-Based Systems by Multi-Objective Evolutionary Learning in high-dimensional regression problems

Francisco Herrera, Rafael Alcalá, María José Gacto, 2013, 2013 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).

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

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

IFS-CoCo in the Landscape Contest: Description and Results

Francisco Herrera, Salvador García, Joaquín Derrac, 2010, ICPR Contests.

A cooperative coevolutionary algorithm for jointly learning fuzzy rule bases and membership functions

Francisco Herrera, Jorge Casillas, Oscar Cordón, 2001, EUSFLAT Conf..

Comments on “Interval Type-2 Fuzzy Sets are Generalization of Interval-Valued Fuzzy Sets: Towards a Wide View on Their Relationship”

Jerry M. Mendel, Francisco Herrera, Hani Hagras, 2015, IEEE Transactions on Fuzzy Systems.

A Fast and Scalable Multiobjective Genetic Fuzzy System for Linguistic Fuzzy Modeling in High-Dimensional Regression Problems

Francisco Herrera, Rafael Alcalá, María José Gacto, 2011, IEEE Transactions on Fuzzy Systems.

Multiperson decision-making based on multiplicative preference relations

Francisco Herrera, Enrique Herrera-Viedma, Francisco Chiclana, 2001, Eur. J. Oper. Res..

Integrating three representation models in fuzzy multipurpose decision making based on fuzzy preference relations

Francisco Herrera, Enrique Herrera-Viedma, Francisco Chiclana, 1998, Fuzzy Sets Syst..

Assessing the usefulness of the TKSee software exploration tool

Francisco Herrera, Timothy T. Lethbridge, 2002 .

Stratification for scaling up evolutionary prototype selection

Francisco Herrera, José Ramón Cano, Manuel Lozano, 2005, Pattern Recognit. Lett..

A linguistic decision model for personnel management solved with a linguistic biobjective genetic algorithm

Francisco Herrera, Enrique López, Cristina Mendaña, 2001, Fuzzy Sets Syst..

Automatic handgun detection alarm in videos using deep learning

Francisco Herrera, Siham Tabik, Roberto Olmos, 2017, Neurocomputing.

A Prediction System for Cardiovascularity Diseases Using Genetic Fuzzy Rule-Based Systems

Francisco Herrera, Oscar Cordón, Ana M. Sánchez, 2002, IBERAMIA.

Underground Mining Method Selection With the Hesitant Fuzzy Linguistic Gained and Lost Dominance Score Method

Francisco Herrera, Huchang Liao, Xingli Wu, 2018, IEEE Access.

Hybrid crossover operators with multiple descendents for real‐coded genetic algorithms: Combining neighborhood‐based crossover operators

Francisco Herrera, Ana M. Sánchez, Manuel Lozano, 2009, Int. J. Intell. Syst..

Other Kinds of Evolutionary Fuzzy Systems

Francisco Herrera, Luis Magdalena, Oscar Cordón, 2001 .

A learning process for fuzzy control rules using genetic algorithms

Francisco Herrera, José L. Verdegay, Manuel Lozano, 1998, Fuzzy Sets Syst..

Fast and Scalable Approaches to Accelerate the Fuzzy k-Nearest Neighbors Classifier for Big Data

Francisco Herrera, Salvador García, Julián Luengo, 2020, IEEE Transactions on Fuzzy Systems.

Chi-Spark-RS: An Spark-built evolutionary fuzzy rule selection algorithm in imbalanced classification for big data problems

Francisco Herrera, Alberto Fernández, Eva Almansa, 2017, 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).

A Forecasting Methodology for Workload Forecasting in Cloud Systems

Francisco Herrera, Sergio Ramírez-Gallego, Christoph Bergmeir, 2018, IEEE Transactions on Cloud Computing.

A taxonomy for the crossover operator for real‐coded genetic algorithms: An experimental study

Francisco Herrera, Ana M. Sánchez, Manuel Lozano, 2003, Int. J. Intell. Syst..

Case Studies and Metrics

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

Integrating Instance Selection, Instance Weighting, and Feature Weighting for Nearest Neighbor Classifiers by Coevolutionary Algorithms

Francisco Herrera, Salvador García, Joaquín Derrac, 2012, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

The ordered weighted Geometric operator: properties and application in MCDM problems

Francisco Herrera, Enrique Herrera-Viedma, Francisco Chiclana, 2000 .

Musical genre classification by means of Fuzzy Rule-Based Systems: A preliminary approach

Francisco Herrera, Rafael Alcalá, O FranciscoChávezdela, 2011, 2011 IEEE Congress of Evolutionary Computation (CEC).

Cooperative Coevolution for Learning Fuzzy Rule-Based Systems

Francisco Herrera, Juan Julián Merelo Guervós, Jorge Casillas, 2001, Artificial Evolution.

Multilabel Classification: Problem Analysis, Metrics and Techniques

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

Linguistic Decision Making and Computing with Words

Francisco Herrera, Rosa M. Rodríguez, Luis Martínez, 2015 .

Computing the Spanish Medium Electrical Line Maintenance Costs by means of Evolution-Based Learning Processes

Francisco Herrera, Oscar Cordón, Luciano Sánchez, 1998, IEA/AIE.

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..

BreakHis based breast cancer automatic diagnosis using deep learning: Taxonomy, survey and insights

Francisco Herrera, Siham Tabik, Boujemâa Achchab, 2020, Neurocomputing.

An Analysis of Local and Global Solutions to Address Big Data Imbalanced Classification: A Case Study with SMOTE Preprocessing

Francisco Herrera, Alberto Fernández, Marcelo R. Naiouf, 2019, JCC&BD.

pyDML: A Python Library for Distance Metric Learning

Francisco Herrera, Salvador García, Juan Luis Suárez, 2020, J. Mach. Learn. Res..

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

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

Minimizing adjusted simple terms in the consensus reaching process with hesitant linguistic assessments in group decision making

Francisco Herrera, Yucheng Dong, Xia Chen, 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.

Big Data Preprocessing: Enabling Smart Data

Francisco Herrera, Sergio Ramírez-Gallego, Julián Luengo, 2020 .

Consensus evolution networks: A consensus reaching tool for managing consensus thresholds in group decision making

Francisco Herrera, Jindong Qin, Xinwang Liu, 2019, Inf. Fusion.

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.

Editorial scalability of evolutionary algorithms and other metaheuristics for large-scale continuous optimization problems

Francisco Herrera, Daniel Molina, Manuel Lozano, 2011, Soft Comput..

IFS-CoCo: Instance and feature selection based on cooperative coevolution with nearest neighbor rule

Francisco Herrera, Salvador García, Joaquín Derrac, 2010, Pattern Recognit..

Learning from data using the R package "FRBS"

Francisco Herrera, Lala Septem Riza, José Manuel Benítez, 2014, 2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).

Genetic fuzzy systems. New developments

Francisco Herrera, Luis Magdalena, Oscar Cordón, 2004, Fuzzy Sets Syst..

Special issue on evolutionary fuzzy systems

Francisco Herrera, Hisao Ishibuchi, Rafael Alcalá, 2011, Int. J. Comput. Intell. Syst..

A multigranular hierarchical linguistic model for design evaluation based on safety and cost analysis: Research Articles

Francisco Herrera, Jian-Bo Yang, Jun Liu, 2005 .

Cardinal Consistency of Reciprocal Preference Relations: A Characterization of Multiplicative Transitivity

Francisco Herrera, Enrique Herrera-Viedma, Sergio Alonso, 2009, IEEE Transactions on Fuzzy Systems.

A Double Axis Classification of Interpretability Measures for Linguistic Fuzzy Rule-Based Systems

Francisco Herrera, Rafael Alcalá, María José Gacto, 2011, WILF.

Fuzzy rule based classification systems for big data with MapReduce: granularity analysis

Francisco Herrera, Alberto Fernández, Sara del Río, 2017, Adv. Data Anal. Classif..

On the linguistic OWA operator and extensions

Francisco Herrera, Enrique Herrera-Viedma, F. Herrera, 1997 .

AT-MFCGA: An Adaptive Transfer-guided Multifactorial Cellular Genetic Algorithm for Evolutionary Multitasking pdf

Francisco Herrera, Javier Del Ser, Eneko Osaba, 2020, Inf. Sci..

Managing Monotonicity in Classification by a Pruned Random Forest

Francisco Herrera, Salvador García, Sergio González, 2015, IDEAL.

A Survey on the Application of Genetic Programming to Classification

Francisco Herrera, Sebastián Ventura, Pedro G. Espejo, 2010, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

Linguistic modeling by hierarchical systems of linguistic rules

Francisco Herrera, Oscar Cordón, Igor Zwir, 2002, IEEE Trans. Fuzzy Syst..

Overview of Hesitant Linguistic Preference Relations for Representing Cognitive Complex Information: Where We Stand and What Is Next

Francisco Herrera, Ming Tang, Huchang Liao, 2019, Cognitive Computation.

Hesitancy degree-based correlation measures for hesitant fuzzy linguistic term sets and their applications in multiple criteria decision making

Francisco Herrera, Huchang Liao, Xiao-Jun Zeng, 2020, Inf. Sci..

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.

The 2-Tuple Linguistic Computational Model. Advantages of Its Linguistic Description, Accuracy and Consistency

Francisco Herrera, Luis Martínez-López, F. Herrera, 2001, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

Conference Report on 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2017) [Conference Reports]

Francisco Herrera, Hani Hagras, Bruno Siciliano, 2017, IEEE Comput. Intell. Mag..

New Ordering-Based Pruning Metrics for Ensembles of Classifiers in Imbalanced Datasets

Francisco Herrera, Humberto Bustince, Mikel Galar, 2015, CORES.

A Genetic Algorithm for Feature Selection and Granularity Learning in Fuzzy Rule-Based Classification Systems for Highly Imbalanced Data-Sets

Francisco Herrera, Alberto Fernández, Pedro Villar, 2010, IPMU.

Managing consensus based on leadership in opinion dynamics

Francisco Herrera, Luis Martínez-López, Yucheng Dong, 2017, Inf. Sci..

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.

ROSEFW-RF: The winner algorithm for the ECBDL'14 big data competition: An extremely imbalanced big data bioinformatics problem

Francisco Herrera, Jaume Bacardit, José Manuel Benítez, 2015, Knowl. Based Syst..

Domains of competence of fuzzy rule based classification systems with data complexity measures: A case of study using a fuzzy hybrid genetic based machine learning method

Francisco Herrera, Julián Luengo, F. Herrera, 2010, Fuzzy Sets Syst..

Fuzzy Multi-Instance Classifiers

Francisco Herrera, Chris Cornelis, Sarah Vluymans, 2016, IEEE Transactions on Fuzzy Systems.

Memetic algorithm with Local search chaining for large scale continuous optimization problems

Francisco Herrera, Daniel Molina, Manuel Lozano, 2009, 2009 IEEE Congress on Evolutionary Computation.

Neutrality in the sentiment analysis problem based on fuzzy majority

Francisco Herrera, M. Victoria Luzón, Ana Valdivia, 2017, 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).

Tweet Coupling: a social media methodology for clustering scientific publications

Francisco Herrera, Sebastián Ventura, Umair Ali, 2020, Scientometrics.

A Preliminary Study on the Selection of Generalized Instances for Imbalanced Classification

Francisco Herrera, Salvador García, Cristóbal J. Carmona, 2010, IEA/AIE.

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..

An insight into classification with imbalanced data: Empirical results and current trends on using data intrinsic characteristics

Francisco Herrera, Salvador García, Alberto Fernández, 2013, Inf. Sci..

Consistency of Reciprocal Preference Relations

Francisco Herrera, Enrique Herrera-Viedma, Sergio Alonso, 2007, 2007 IEEE International Fuzzy Systems Conference.

Fuzzy k-Nearest Neighbors with monotonicity constraints: Moving towards the robustness of monotonic noise pdf

Francisco Herrera, Sheng-Tun Li, Robert John, 2020, Neurocomputing.

Evolutionary stratified training set selection for extracting classification rules with trade off precision-interpretability

Francisco Herrera, José Ramón Cano, Manuel Lozano, 2007, Data Knowl. Eng..

rNPBST: An R Package Covering Non-parametric and Bayesian Statistical Tests

Francisco Herrera, Salvador García, María del Mar Rueda, 2017, HAIS.

Ruta: Implementations of neural autoencoders in R

Francisco Charte, Francisco Herrera, David Charte, 2019, Knowl. Based Syst..

Deriving the priority weights from incomplete hesitant fuzzy preference relations in group decision making

Yejun Xu, Francisco Herrera, Lei Chen, 2016, Knowl. Based Syst..

IFROWANN: Imbalanced Fuzzy-Rough Ordered Weighted Average Nearest Neighbor Classification

Francisco Herrera, Chris Cornelis, Sarah Vluymans, 2015, IEEE Transactions on Fuzzy Systems.

A First Approach to Nearest Hyperrectangle Selection by Evolutionary Algorithms

Francisco Herrera, Salvador García, Joaquín Derrac, 2009, 2009 Ninth International Conference on Intelligent Systems Design and Applications.

Learning from Imbalanced Data Streams

Francisco Herrera, Mikel Galar, Salvador García, 2018 .

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..

On the usefulness of one-class classifier ensembles for decomposition of multi-class problems

Francisco Herrera, Bartosz Krawczyk, Michal Wozniak, 2015, Pattern Recognit..

Irony detection in Twitter with imbalanced class distributions

Francisco Herrera, Paolo Rosso, Ronaldo C. Prati, 2020, J. Intell. Fuzzy Syst..

Genetic Fuzzy Rule-Based Systems Based on the Pittsburgh Approach

Francisco Herrera, Luis Magdalena, Oscar Cordón, 2001 .

Genetic Fuzzy Systems: Status, Critical Considerations and Future Directions

Francisco Herrera, F. Herrera, 2005 .

Missing data imputation for fuzzy rule-based classification systems

Francisco Herrera, Julián Luengo, José A. Sáez, 2012, Soft Comput..

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.

SMOTE for Learning from Imbalanced Data: Progress and Challenges, Marking the 15-year Anniversary

Francisco Herrera, Nitesh V. Chawla, Salvador García, 2018, J. Artif. Intell. Res..

Personalized individual semantics based on consistency in hesitant linguistic group decision making with comparative linguistic expressions

Francisco Herrera, Luis Martínez, Yucheng Dong, 2018, Knowl. Based Syst..

DRCW-OVO: Distance-based relative competence weighting combination for One-vs-One strategy in multi-class problems

Francisco Herrera, Mikel Galar, Edurne Barrenechea Tartas, 2015, Pattern Recognit..

Sentiment Analysis on TripAdvisor: Are There Inconsistencies in User Reviews?

Francisco Herrera, M. Victoria Luzón, Ana Valdivia, 2017, HAIS.

A preliminary study on Hybrid Spill-Tree Fuzzy k-Nearest Neighbors for big data classification

Francisco Herrera, Salvador García, Julián Luengo, 2018, 2018 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).

Integration of an Index to Preserve the Semantic Interpretability in the Multiobjective Evolutionary Rule Selection and Tuning of Linguistic Fuzzy Systems

Francisco Herrera, Rafael Alcalá, María José Gacto, 2010, IEEE Transactions on Fuzzy Systems.

Adaptation and application of multi-objective evolutionary algorithms for rule reduction and parameter tuning of fuzzy rule-based systems

Francisco Herrera, Rafael Alcalá, María José Gacto, 2008, 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..

Evolutionary Training Set Selection to Optimize C4.5 in Imbalanced Problems

Francisco Herrera, Salvador García, S. García, 2008, 2008 Eighth International Conference on Hybrid Intelligent 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.

A Review on Evolutionary Prototype Selection

Francisco Herrera, José Ramón Cano, Salvador García, 2010, Intelligent Systems for Automated Learning and Adaptation.

Dealing with Difficult Minority Labels in Imbalanced Mutilabel Data Sets

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

Smart Data based Ensemble for Imbalanced Big Data Classification pdf

Francisco Herrera, Ning Xiong, Diego García-Gil, 2020, ArXiv.

Fuzzy linguistic ranking model for web accessibility test tools

Francisco Herrera, Rosana Montes Soldado, Noe Zermeño, 2018 .

A multi-instance learning wrapper based on the Rocchio classifier for web index recommendation

Francisco Herrera, Chris Cornelis, Rafael Bello, 2014, Knowl. Based Syst..

Chain based sampling for monotonic imbalanced classification

Francisco Herrera, Salvador García, Sheng-Tun Li, 2019, Inf. Sci..

Advanced nonparametric tests for multiple comparisons in the design of experiments in computational intelligence and data mining: Experimental analysis of power

Francisco Herrera, Salvador García, Alberto Fernández, 2010, Inf. Sci..

Non-classical Imbalanced Classification Problems

Francisco Herrera, Mikel Galar, Salvador García, 2018 .

Self-labeled techniques for semi-supervised learning: taxonomy, software and empirical study

Francisco Herrera, Salvador García, Isaac Triguero, 2015, Knowledge and Information Systems.

Addressing imbalanced classification with instance generation techniques: IPADE-ID

Francisco Herrera, Salvador García, Cristóbal J. Carmona, 2014, Neurocomputing.

Evolutionary Multi-Objective Algorithm to effectively improve the performance of the classic tuning of fuzzy logic controllers for a heating, ventilating and Air Conditioning system

Francisco Herrera, Rafael Alcalá, María José Gacto, 2011, 2011 IEEE 5th International Workshop on Genetic and Evolutionary Fuzzy Systems (GEFS).

Solving an assignment-selection problem with verbal information and using genetic algorithms

Francisco Herrera, Enrique López, Cristina Mendaña, 1999, Eur. J. Oper. Res..

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..

Large-scale group decision making model based on social network analysis: Trust relationship-based conflict detection and elimination

Francisco Herrera, Iván Palomares, Ru-Xi Ding, 2019, Eur. J. Oper. Res..

Multiple Instance Learning

Francisco Herrera, Chris Cornelis, Sarah Vluymans, 2016 .

WoS query partitioner: A tool to retrieve very large numbers of items from the Web of Science using different source-based partitioning approaches

Francisco Herrera, Enrique Herrera-Viedma, Francisco Javier Cabrerizo, 2010, J. Assoc. Inf. Sci. Technol..

Sentiment Analysis based Multi-Person Multi-criteria Decision Making methodology using natural language processing and deep learning for smarter decision aid. Case study of restaurant choice using TripAdvisor reviews

Francisco Herrera, Enrique Herrera-Viedma, Cristina Zuheros, 2020, Inf. Fusion.

Consensus reaching process for large-scale group decision making with double hierarchy hesitant fuzzy linguistic preference relations

Francisco Herrera, Zeshui Xu, Xunjie Gou, 2018, Knowl. Based Syst..

Redundancy and Complexity Metrics for Big Data Classification: Towards Smart Data

Francisco Herrera, Isaac Triguero, Jesus Maillo, 2020, IEEE Access.

Data Sets and Proper Statistical Analysis of Data Mining Techniques

Francisco Herrera, Salvador García, Julián Luengo, 2015 .

Improving Simple Linguistic Fuzzy Models by Means of the Weighted COR Methodology

Francisco Herrera, Rafael Alcalá, Jorge Casillas, 2002, IBERAMIA.

Improving the Performance of FARC-HD in Multi-class Classification Problems Using the One-Versus-One Strategy and an Adaptation of the Inference System

Francisco Herrera, Humberto Bustince, Mikel Galar, 2014, IPMU.

Author's reply [to comments on 'A proposal to improve the accuracy of linguistic modelling']

Francisco Herrera, Oscar Cordón, 2003, IEEE Trans. Fuzzy Syst..

8th International Conference on Hybrid Intelligent Systems (HIS 2008), September 10-12, 2008, Barcelona, Spain

Francisco Herrera, Fatos Xhafa, Ajith Abraham, 2008, HIS.

An overview on subgroup discovery: foundations and applications

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

Some induced ordered weighted averaging operators and their use for solving group decision-making problems based on fuzzy preference relations

Francisco Herrera, Enrique Herrera-Viedma, Sergio Alonso, 2007, Eur. J. Oper. Res..

A Multi-Objective Genetic Algorithm for Tuning and Rule Selection to Obtain Accurate and Compact Linguistic Fuzzy Rule-Based Systems

Francisco Herrera, Jesús Alcalá-Fdez, Rafael Alcalá, 2007, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

Hesitant Fuzzy Sets: State of the Art and Future Directions

Francisco Herrera, Zeshui Xu, Luis Martínez-López, 2014, Int. J. Intell. Syst..

Evolutionary wrapper approaches for training set selection as preprocessing mechanism for support vector machines: Experimental evaluation and support vector analysis

Francisco Herrera, Chris Cornelis, Salvador García, 2016, Appl. Soft Comput..

Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI pdf

Francisco Herrera, Javier Del Ser, Richard Benjamins, 2020, Inf. Fusion.

Visualizing and rectifying different inconsistencies for fuzzy reciprocal preference relations

Yejun Xu, Francisco Herrera, F. Herrera, 2019, Fuzzy Sets Syst..

NICGAR: A Niching Genetic Algorithm to mine a diverse set of interesting quantitative association rules

Francisco Herrera, Jesús Alcalá-Fdez, Alejandro Rosete, 2016, Inf. Sci..

Cooperative Evolutionary Learning of Linguistic Fuzzy Rules and Parametric Aggregation Connectors for Mamdani Fuzzy Systems

Francisco Herrera, Francisco Alfredo Márquez, Antonio Peregrín, 2007, IEEE Transactions on Fuzzy Systems.

Fast Case-Based Reasoning for Large-Scale Streaming Classification

Francisco Herrera, Bartosz Krawczyk, José Manuel Benítez, 2017 .

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 note on the reciprocity in the aggregation of fuzzy preference relations using OWA operators

Francisco Herrera, Luis Martínez-López, Enrique Herrera-Viedma, 2003, Fuzzy Sets Syst..

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.

Linguistic group decision making: Axiomatic distance and minimum cost consensus

Francisco Herrera, Yucheng Dong, Yao Li, 2020, Inf. Sci..

QAR-CIP-NSGA-II: A new multi-objective evolutionary algorithm to mine quantitative association rules

Francisco Herrera, Jesús Alcalá-Fdez, Alejandro Rosete, 2014, Inf. Sci..

Analysis and guidelines to obtain a good uniform fuzzy partition granularity for fuzzy rule-based systems using simulated annealing

Francisco Herrera, Oscar Cordón, Pedro Villar, 2000, Int. J. Approx. Reason..

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..

Analysis of the efficacy of a Two-Stage methodology for ant colony optimization: Case of study with TSP and QAP

Francisco Herrera, Rafael Bello, Amilkar Puris, 2010, Expert Syst. Appl..

A preliminary study on fingerprint classification using fuzzy rule-based classification systems

Francisco Herrera, Humberto Bustince, Mikel Galar, 2014, 2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).

A multigranular hierarchical linguistic model for design evaluation based on safety and cost analysis

Francisco Herrera, Jian-Bo Yang, Jun Liu, 2005, Int. J. Intell. Syst..

Improving the Behavior of the Nearest Neighbor Classifier against Noisy Data with Feature Weighting Schemes

Francisco Herrera, Joaquín Derrac, Julián Luengo, 2014, HAIS.

Genetic Learning of the Knowledge Base of a Fuzzy System by Using the Linguistic 2-Tuples Representation

Francisco Herrera, Jesús Alcalá-Fdez, Rafael Alcalá, 2005, The 14th IEEE International Conference on Fuzzy Systems, 2005. FUZZ '05..

A proposal for evolutionary fuzzy systems using feature weighting: Dealing with overlapping in imbalanced datasets

Francisco Herrera, Alberto Fernández, Saleh Alshomrani, 2015, Knowl. Based Syst..

A fuzzy model to evaluate the suitability of installing an enterprise resource planning system

Francisco Herrera, Luis Martínez-López, Enrique Herrera-Viedma, 2009, Inf. Sci..

A New Multiobjective Evolutionary Algorithm for Mining a Reduced Set of Interesting Positive and Negative Quantitative Association Rules

Francisco Herrera, Jesús Alcalá-Fdez, Alejandro Rosete, 2014, IEEE Transactions on Evolutionary Computation.

Preference modelling and applications: Selected papers from EUROFUSE 2001, Granada

Francisco Herrera, Bernard De Baets, Luis Martínez-López, 2003, Fuzzy Sets Syst..

An Overview on the Structure and Applications for Business Intelligence and Data Mining in Cloud Computing

Francisco Herrera, Alberto Fernández, José Manuel Benítez, 2012, KMO.

On the impact of Distance-based Relative Competence Weighting approach in One-vs-One classification for Evolutionary Fuzzy Systems: DRCW-FH-GBML algorithm

Francisco Herrera, Humberto Bustince, Oscar Cordón, 2015, 2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).

Fuzzy Sets and Their Extensions: Representation, Aggregation and Models - Intelligent Systems from Decision Making to Data Mining, Web Intelligence and Computer Vision

Francisco Herrera, Humberto Bustince, Javier Montero, 2007, Fuzzy Sets and Their Extensions: Representation, Aggregation and Models.

A study on the use of non-parametric tests for analyzing the evolutionary algorithms’ behaviour: a case study on the CEC’2005 Special Session on Real Parameter Optimization

Francisco Herrera, Salvador García, Daniel Molina, 2009, J. Heuristics.

Induced ordered weighted geometric operators and their use in the aggregation of multiplicative preference relations

Francisco Herrera, Enrique Herrera-Viedma, Sergio Alonso, 2004, Int. J. Intell. Syst..

Multivariate Discretization Based on Evolutionary Cut Points Selection for Classification

Francisco Herrera, Sergio Ramírez-Gallego, José Manuel Benítez, 2016, IEEE Transactions on Cybernetics.

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..

A study of statistical techniques and performance measures for genetics-based machine learning: accuracy and interpretability

Francisco Herrera, Salvador García, Alberto Fernández, 2009, Soft Comput..

A consistency-driven approach to set personalized numerical scales for hesitant fuzzy linguistic preference relations

Francisco Herrera, Luis Martínez, Yucheng Dong, 2017, 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).

A first approach towards a fuzzy decision tree for multilabel classification

Francisco Charte, Francisco Herrera, Ronaldo C. Prati, 2017, 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).

On the Usefulness of MOEAs for Getting Compact FRBSs Under Parameter Tuning and Rule Selection

Francisco Herrera, Jesús Alcalá-Fdez, Rafael Alcalá, 2008, Multi-Objective Evolutionary Algorithms for Knowledge Discovery from Databases.

Replacement strategies to preserve useful diversity in steady-state genetic algorithms

Francisco Herrera, José Ramón Cano, Manuel Lozano, 2008, Inf. Sci..

Genetic Fuzzy Rule-Based Systems Based on the Iterative Rule Learning Approach

Francisco Herrera, Luis Magdalena, Oscar Cordón, 2001 .

Special issue on hybrid artificial intelligence systems from the HAIS 2017 conference - Editorial

Francisco Herrera, Emilio Corchado, Ajith Abraham, 2019, Neurocomputing.

A genetic algorithm for tuning fuzzy rule-based classification systems with Interval-Valued Fuzzy Sets

Francisco Herrera, Humberto Bustince, Alberto Fernández, 2010, International Conference on Fuzzy Systems.

otsad: A package for online time-series anomaly detectors

Francisco Herrera, Angel Conde, Jacinto Carrasco, 2020, Neurocomputing.

ON GROUP DECISION MAKING UNDER LINGUISTIC PREFERENCES AND FUZZY LINGUISTIC QUANTIFIERS

Francisco Herrera, J. Luis Verdegay, F. Herrera, 1995 .

Adaptic Control of the Mutation Probability by Fuzzy Logic Controllers

Francisco Herrera, Manuel Lozano, F. Herrera, 2000, PPSN.

Dealing with Missing Values

Francisco Herrera, Salvador García, Julián Luengo, 2015 .

A combined MapReduce-windowing two-level parallel scheme for evolutionary prototype generation

Francisco Herrera, Salvador García, Jaume Bacardit, 2014, 2014 IEEE Congress on Evolutionary Computation (CEC).

A First Study on the Use of Noise Filtering to Clean the Bags in Multi-Instance Classification

Francisco Herrera, Ronaldo C. Prati, Julián Luengo, 2018, LOPAL '18.

Linguistic Approaches Based on the 2-Tuple Fuzzy Linguistic Representation Model

Francisco Herrera, Rosa M. Rodríguez, Luis Martínez, 2015 .

Making CN2-SD subgroup discovery algorithm scalable to large size data sets using instance selection

Francisco Herrera, José Ramón Cano, Salvador García, 2008, Expert Syst. Appl..

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.

Enhancing evolutionary instance selection algorithms by means of fuzzy rough set based feature selection

Francisco Herrera, Chris Cornelis, Salvador García, 2012, Inf. Sci..

Imbalanced Multi-instance Data

Francisco Herrera, Chris Cornelis, Sarah Vluymans, 2016 .

Managing non-homogeneous information in group decision making

Francisco Herrera, Luis Martínez-López, Pedro J. Sánchez, 2005, Eur. J. Oper. Res..

Deep-learning Versus OBIA for Scattered Shrub Detection with Google Earth Imagery: Ziziphus lotus as Case Study

Francisco Herrera, Siham Tabik, Domingo Alcaraz-Segura, 2017, Remote. Sens..

Variable mesh optimization for the 2013 CEC Special Session Niching Methods for Multimodal Optimization

Francisco Herrera, Rafael Bello, Daniel Molina, 2013, 2013 IEEE Congress on Evolutionary Computation.

On the characterization of noise filters for self-training semi-supervised in nearest neighbor classification

Francisco Herrera, Salvador García, Julián Luengo, 2014, Neurocomputing.

Interval Type-2 Fuzzy Sets are Generalization of Interval-Valued Fuzzy Sets: Toward a Wider View on Their Relationship

Francisco Herrera, Hani Hagras, Humberto Bustince, 2015, IEEE Transactions on Fuzzy Systems.

A Preliminary Study on Selecting the Optimal Cut Points in Discretization by Evolutionary Algorithms

Francisco Herrera, Salvador García, Cristóbal J. Carmona, 2012, ICPRAM.

A preliminary study on the use of differential evolution for adjusting the position of examples in nearest neighbor classification

Francisco Herrera, Salvador García, Isaac Triguero, 2010, IEEE Congress on Evolutionary Computation.

Construction of consistent fuzzy preference relations using uninorms

Francisco Herrera, Enrique Herrera-Viedma, Sergio Alonso, 2008, 2008 IEEE International Conference on Fuzzy Systems (IEEE World Congress on Computational Intelligence).

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).

Linguistic modeling with weighted double-consequent fuzzy rules based on cooperative coevolution

Francisco Herrera, Rafael Alcalá, Jorge Casillas, 2003, EUSFLAT Conf..

Evolutionary Induction of Descriptive Rules in a Market Problem

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

Guest editors' introduction: special issue on fuzzy approaches in preference modelling, decision making and applications

Francisco Herrera, Enrique Herrera-Viedma, Sergio Alonso, 2008 .

Tree Cover Estimation in Global Drylands from Space Using Deep Learning

Francisco Herrera, Siham Tabik, Javier Cabello, 2020, Remote. Sens..

A First Study on the Use of Coevolutionary Algorithms for Instance and Feature Selection

Francisco Herrera, Salvador García, Joaquín Derrac, 2009, HAIS.

A study of the use of multi-objective evolutionary algorithms to learn Boolean queries: A comparative study

Francisco Herrera, Enrique Herrera-Viedma, Antonio Gabriel López-Herrera, 2009 .

A study on the use of statistical tests for experimentation with neural networks: Analysis of parametric test conditions and non-parametric tests

Francisco Herrera, Salvador García, Julián Luengo, 2007, Expert Syst. Appl..

Data Intrinsic Characteristics

Francisco Herrera, Mikel Galar, Salvador García, 2018 .

Object Detection Binary Classifiers methodology based on deep learning to identify small objects handled similarly: Application in video surveillance

Francisco Herrera, Hamido Fujita, Siham Tabik, 2020, Knowl. Based Syst..

Enhancing difficult classes in one-vs-one classifier fusion strategy using restricted equivalence functions

Francisco Herrera, Mikel Galar, Edurne Barrenechea Tartas, 2014, 17th International Conference on Information Fusion (FUSION).

Region based memetic algorithm with LS chaining

Francisco Herrera, Daniel Molina, Benjamin Lacroix, 2012, 2012 IEEE Congress on Evolutionary Computation.

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.

On the combination of genetic fuzzy systems and pairwise learning for improving detection rates on Intrusion Detection Systems

Francisco Herrera, Alberto Fernández, Saleh Alshomrani, 2015, Expert Syst. Appl..

A Fuzzy Linguistic Methodology to Deal With Unbalanced Linguistic Term Sets

Francisco Herrera, Luis Martínez-López, Enrique Herrera-Viedma, 2008, IEEE Transactions on Fuzzy Systems.

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..

Hesitant Fuzzy Linguistic Analytic Hierarchical Process With Prioritization, Consistency Checking, and Inconsistency Repairing

Ming Tang, Francisco Herrera, Huchang Liao, 2019, IEEE Access.

DPD-DFF: A dual phase distributed scheme with double fingerprint fusion for fast and accurate identification in large databases

Francisco Herrera, Salvador García, Daniel Peralta, 2016, Inf. Fusion.

A first study on the noise impact in classes for Fuzzy Rule Based Classification Systems

Francisco Herrera, Jose A. Saez, José A. Sáez, 2010, 2010 IEEE International Conference on Intelligent Systems and Knowledge Engineering.

SMOTE-RSB*: a hybrid preprocessing approach based on oversampling and undersampling for high imbalanced data-sets using SMOTE and rough sets theory

Francisco Herrera, Rafael Bello, Enislay Ramentol, 2012, Knowledge and Information Systems.

Double hierarchy hesitant fuzzy linguistic term set and MULTIMOORA method: A case of study to evaluate the implementation status of haze controlling measures

Francisco Herrera, Zeshui Xu, Huchang Liao, 2017, Inf. Fusion.

Consensus under a fuzzy context: Taxonomy, analysis framework AFRYCA and experimental case of study

Francisco Herrera, Luis Martínez-López, Iván Palomares, 2014, Inf. Fusion.

Artificial intelligence within the interplay between natural and artificial computation: Advances in data science, trends and applications

Francisco Herrera, Richard J. Duro, Paulo Novais, 2020, Neurocomputing.

Homogeneous Linear fuzzy Functions and Ranking Methods in fuzzy Linear Programming Problems

Francisco Herrera, José L. Verdegay, Margit Kovács, 1994, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

A tutorial on distance metric learning: Mathematical foundations, algorithms, experimental analysis, prospects and challenges

Francisco Herrera, Juan Luis Su'arez-D'iaz, Salvador Garc'ia, 2018, Neurocomputing.

Deep-Learning Convolutional Neural Networks for scattered shrub detection with Google Earth Imagery pdf

Francisco Herrera, Siham Tabik, Domingo Alcaraz-Segura, 2017, ArXiv.

Imbalanced Classification for Big Data

Francisco Herrera, Mikel Galar, Salvador García, 2018 .

Instance reduction for one-class classification

Francisco Herrera, Salvador García, Bartosz Krawczyk, 2018, Knowledge and Information Systems.

Variable mesh optimization for continuous optimization problems

Francisco Herrera, Rafael Bello, Daniel Molina, 2012, Soft Comput..

A genetic learning process for the scaling factors, granularity and contexts of the fuzzy rule-based system data base

Francisco Herrera, Luis Magdalena, Oscar Cordón, 2001, Inf. Sci..

Evolutionary parallel and gradually distributed lateral tuning of fuzzy rule-based systems

Francisco Herrera, Rafael Alcalá, José Manuel Benítez, 2009, Evol. Intell..

Design Of A Control Rules Base Based On Genetic Algorithms

Francisco Herrera, Manuel Lozano, José L. Verdegay, 1995 .

Genetic adaption of rule connectives and conjunction operators in fuzzy rule based systems: an experimental comparative study

Francisco Herrera, Francisco Alfredo Márquez, Antonio Peregrín, 2003, EUSFLAT Conf..

Domains of Competence of Artificial Neural Networks Using Measures of Separability of Classes

Francisco Herrera, Julián Luengo, F. Herrera, 2009, IWANN.

A fusion approach for managing multi-granularity linguistic term sets in decision making

Francisco Herrera, Luis Martínez-López, Enrique Herrera-Viedma, 2000, Fuzzy Sets Syst..

ALM: A Methodology for Designing Accurate Linguistic Models for Intelligent Data Analysis

Francisco Herrera, Oscar Cordón, F. Herrera, 1999, IDA.

Construction of Interval-Valued Fuzzy Preference Relations Using Ignorance Functions: Interval-Valued Non Dominance Criterion

Francisco Herrera, Humberto Bustince, Edurne Barrenechea Tartas, 2011, Eurofuse.

IVTURS: A Linguistic Fuzzy Rule-Based Classification System Based On a New Interval-Valued Fuzzy Reasoning Method With Tuning and Rule Selection

Francisco Herrera, Humberto Bustince, Alberto Fernández, 2013, IEEE Transactions on Fuzzy Systems.

Fuzzy Sets and Their Extensions: Representation, Aggregation and Models

Francisco Herrera, Humberto Bustince, Javier Montero, 2008 .

Introduction to the Experimental Design in the Data Mining Tool KEEL

Francisco Herrera, Jesús Alcalá-Fdez, Luciano Sánchez, 2010 .

Dealing with Hesitant Fuzzy Linguistic Information in Decision Making

Francisco Herrera, Rosa M. Rodríguez, Luis Martínez, 2015 .

E-learning and educational data mining in cloud computing: an overview

Francisco Herrera, Alberto Fernández, Daniel Peralta, 2014, Int. J. Learn. Technol..

An overview on managing additive consistency of reciprocal preference relations for consistency-driven decision making and fusion: Taxonomy and future directions

Yejun Xu, Francisco Herrera, Enrique Herrera-Viedma, 2019, Inf. Fusion.

A genetic tuning to improve the performance of Fuzzy Rule-Based Classification Systems with Interval-Valued Fuzzy Sets: Degree of ignorance and lateral position

Francisco Herrera, Humberto Bustince, Alberto Fernández, 2011, Int. J. Approx. Reason..

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.

R Ultimate Multilabel Dataset Repository

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

Predicting literature's early impact with sentiment analysis in Twitter

Francisco Herrera, Sebastián Ventura, Saeed-Ul Hassan, 2020, Knowl. Based Syst..

Big data preprocessing: methods and prospects

Francisco Herrera, Sergio Ramírez-Gallego, José Manuel Benítez, 2016 .

Ensembles of cost-diverse Bayesian neural learners for imbalanced binary classification

Francisco Herrera, Aníbal R. Figueiras-Vidal, Marcelino Lázaro, 2020, Inf. Sci..

A novel methodology to classify test cases using natural language processing and imbalanced learning

Francisco Herrera, Wasif Afzal, Enislay Ramentol, 2020, Eng. Appl. Artif. Intell..

Real-Coded Memetic Algorithms with Crossover Hill-Climbing

Francisco Herrera, Daniel Molina, Natalio Krasnogor, 2004, Evolutionary Computation.

A multi-objective evolutionary fuzzy system to obtain a broad and accurate set of solutions in intrusion detection systems

Francisco Herrera, Abdulrahman H. Altalhi, Alberto Fernández, 2019, Soft Comput..

INFFC: An iterative class noise filter based on the fusion of classifiers with noise sensitivity control

Francisco Herrera, Mikel Galar, Julián Luengo, 2016, Inf. Fusion.

Interval MULTIMOORA Method Integrating Interval Borda Rule and Interval Best–Worst-Method-Based Weighting Model: Case Study on Hybrid Vehicle Engine Selection

Francisco Herrera, Huchang Liao, Ashkan Hafezalkotob, 2020, IEEE Transactions on Cybernetics.

A Preliminary Study of the Feasibility of Global Evolutionary Feature Selection for Big Datasets under Apache Spark

Francisco Herrera, Humberto Bustince, Mikel Galar, 2018, 2018 IEEE Congress on Evolutionary Computation (CEC).

E2SAM: Evolutionary ensemble of sentiment analysis methods for domain adaptation

Francisco Herrera, Miguel López, M. Victoria Luzón, 2019, Inf. Sci..

A practical tutorial on bagging and boosting based ensembles for machine learning: Algorithms, software tools, performance study, practical perspectives and opportunities

Francisco Herrera, Lior Rokach, Salvador García, 2020, Inf. Fusion.

Analyze, Sense, Preprocess, Predict, Implement, and Deploy (ASPPID): An incremental methodology based on data analytics for cost-efficiently monitoring the industry 4.0

Francisco Herrera, Javier Del Ser, Antonio J. Nebro, 2019, Eng. Appl. Artif. Intell..

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.

Influence of regions on the memetic algorithm for the CEC'2014 Special Session on Real-Parameter Single Objective Optimisation

Francisco Herrera, Daniel Molina, Benjamin Lacroix, 2014, 2014 IEEE Congress on Evolutionary Computation (CEC).

Foundations on Imbalanced Classification

Francisco Herrera, Mikel Galar, Salvador García, 2018 .

Imbalance in Multilabel Datasets

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

Analyzing convergence performance of evolutionary algorithms: A statistical approach

Francisco Herrera, Salvador García, Ponnuthurai N. Suganthan, 2014, Inf. Sci..

LUNAR: Cellular Automata for Drifting Data Streams

Francisco Herrera, Javier Del Ser, Jesus L. Lobo, 2020, Inf. Sci..

Feature Selection Algorithms Applied to Parkinson's Disease

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

A study on the application of instance selection techniques in genetic fuzzy rule-based classification systems: Accuracy-complexity trade-off

Francisco Herrera, Rafael Alcalá, Francesco Marcelloni, 2013, Knowl. Based Syst..

On the use of evolutionary feature selection for improving fuzzy rough set based prototype selection

Francisco Herrera, Chris Cornelis, Salvador García, 2012, Soft Computing.

Continuous scatter search: An analysis of the integration of some combination methods and improvement strategies

Francisco Herrera, Daniel Molina, Manuel Lozano, 2006, Eur. J. Oper. Res..

Grouping, Overlap, and Generalized Bientropic Functions for Fuzzy Modeling of Pairwise Comparisons

Eyke Hüllermeier, Francisco Herrera, Humberto Bustince, 2012, IEEE Transactions on Fuzzy Systems.

A Survey of Discretization Techniques: Taxonomy and Empirical Analysis in Supervised Learning

Francisco Herrera, Salvador García, Julián Luengo, 2013, IEEE Transactions on Knowledge and Data Engineering.

Linguistic decision analysis: steps for solving decision problems under linguistic information

Francisco Herrera, Enrique Herrera-Viedma, F. Herrera, 2000, Fuzzy Sets Syst..

Modeling agent‐based consumers decision‐making with 2‐tuple fuzzy linguistic perceptions

Francisco Herrera, Oscar Cordón, Jesús Giráldez-Cru, 2019, Int. J. Intell. Syst..

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 Consensus Model to Detect and Manage Noncooperative Behaviors in Large-Scale Group Decision Making

Francisco Herrera, Luis Martínez-López, Iván Palomares, 2014, IEEE Transactions on Fuzzy Systems.

Tutorial on practical tips of the most influential data preprocessing algorithms in data mining

Francisco Herrera, Salvador García, Julián Luengo, 2016, Knowl. Based Syst..

Bag-Based Classification Methods

Francisco Herrera, Chris Cornelis, Sarah Vluymans, 2016 .

Learning from Imbalanced Data Sets

Francisco Herrera, Mikel Galar, Salvador García, 2018, Springer International Publishing.

An overview of MULTIMOORA for multi-criteria decision-making: Theory, developments, applications, and challenges

Francisco Herrera, Ashkan Hafezalkotob, Arian Hafezalkotob, 2019, Inf. Fusion.

Tackling Real-Coded Genetic Algorithms: Operators and Tools for Behavioural Analysis

Francisco Herrera, José L. Verdegay, Manuel Lozano, 1998, Artificial Intelligence Review.

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..

Fuzzy Evolutionary Algorithms and Genetic Fuzzy Systems: A Positive Collaboration between Evolutionary Algorithms and Fuzzy Systems

Francisco Herrera, M. Lozano, F. Herrera, 2009 .

Enhancing evolutionary fuzzy systems for multi-class problems: Distance-based relative competence weighting with truncated confidences (DRCW-TC)

Francisco Herrera, Humberto Bustince, Mikel Galar, 2016, Int. J. Approx. Reason..

Prototype Selection for Nearest Neighbor Classification: Taxonomy and Empirical Study

Francisco Herrera, José Ramón Cano, Salvador García, 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.

A multi-objective evolutionary approach to training set selection for support vector machine

Francisco Herrera, Genny Tortora, Giovanni Acampora, 2018, Knowl. Based Syst..

Whale counting in satellite and aerial images with deep learning

Francisco Herrera, Siham Tabik, Domingo Alcaraz-Segura, 2019, Scientific Reports.

Fuzzy connectives based crossover operators to model genetic algorithms population diversity

Francisco Herrera, José L. Verdegay, Manuel Lozano, 1997, Fuzzy Sets Syst..

Cognitive Computing: Architecture, Technologies and Intelligent Applications

Francisco Herrera, Min Chen, Kai Hwang, 2018, IEEE Access.

Genetic Fuzzy Rule-Based Systems Based on the Michigan Approach

Francisco Herrera, Luis Magdalena, Oscar Cordón, 2001 .

A Multicriteria Linguistic Decision Making Model Dealing with Comparative Terms

Francisco Herrera, Luis Martínez, Rosa M. Rodríguez, 2011, Eurofuse.

A continuous interval-valued linguistic ORESTE method for multi-criteria group decision making

Francisco Herrera, Jian-Bo Yang, Huchang Liao, 2018, Knowl. Based Syst..

A First Study on Decomposition Strategies with Data with Class Noise Using Decision Trees

Francisco Herrera, Mikel Galar, Julián Luengo, 2012, HAIS.

Alternative Ranking-Based Clustering and Reliability Index-Based Consensus Reaching Process for Hesitant Fuzzy Large Scale Group Decision Making

Yejun Xu, Francisco Herrera, Ru-Xi Ding, 2019, IEEE Transactions on Fuzzy Systems.

Combining Numerical and Linguistic Information in Group Decision Making

Francisco Herrera, Luis Martínez-López, Enrique Herrera-Viedma, 1998, Inf. Sci..

The NoiseFiltersR Package: Label Noise Preprocessing in R

Francisco Herrera, Ana Carolina Lorena, André C. P. L. F. de Carvalho, 2017, R J..

Special issue on genetic fuzzy systems for control and robotics-- Preface

Francisco Herrera, 1997, Int. J. Approx. Reason..

Analysis of the Best-Worst Ant System and Its Variants on the QAP

Francisco Herrera, Oscar Cordón, Iñaki Fernández de Viana, 2002, Ant Algorithms.

Region based memetic algorithm for real-parameter optimisation

Francisco Herrera, Daniel Molina, Benjamin Lacroix, 2014, Inf. Sci..

A greedy randomized adaptive search procedure applied to the clustering problem as an initialization process using K-Means as a local search procedure

Francisco Herrera, Oscar Cordón, José Ramón Cano, 2002, J. Intell. Fuzzy Syst..

A Review of Fingerprint Feature Representations and Their Applications for Latent Fingerprint Identification: Trends and Evaluation

Francisco Herrera, Aythami Morales, Raúl Monroy, 2019, IEEE Access.

A survey of fingerprint classification Part II

Francisco Herrera, Humberto Bustince, Carlos Lopez-Molina, 2015 .

Analysis of Data Preprocessing Increasing the Oversampling Ratio for Extremely Imbalanced Big Data Classification

Francisco Herrera, José Manuel Benítez, Sara del Río, 2015, 2015 IEEE Trustcom/BigDataSE/ISPA.

A consistency‐based procedure to estimate missing pairwise preference values

Francisco Herrera, Jesús Alcalá-Fdez, Enrique Herrera-Viedma, 2008, Int. J. Intell. Syst..

Fingerprint classification with a new deep neural network model: robustness for different captures of the same fingerprints pdf

Francisco Herrera, Yvan Saeys, Salvador García, 2017, ArXiv.

Proceedings of the 23rd international conference on Industrial engineering and other applications of applied intelligent systems - Volume Part III

Francisco Herrera, Colin Fyfe, Moonis Ali, 2010 .

A Review of Hesitant Fuzzy Sets: Quantitative and Qualitative Extensions

Francisco Herrera, Luis Martínez-López, Vicenç Torra, 2016, Fuzzy Logic in Its 50th Year.

On the Usefulness of Interval Valued Fuzzy Sets for Learning Fuzzy Rule Based Classification Systems

Francisco Herrera, F. Herrera, 2011, Eurofuse.

Multiple Instance Multiple Label Learning

Francisco Herrera, Chris Cornelis, Sarah Vluymans, 2016 .

FRPS: A Fuzzy Rough Prototype Selection method

Francisco Herrera, Chris Cornelis, Nele Verbiest, 2013, Pattern Recognit..

Editorial: Trust Management for Multimedia Big Data

Francisco Herrera, Robert H. Deng, Jun Liu, 2016, ACM Trans. Multim. Comput. Commun. Appl..

Improving SMOTE with Fuzzy Rough Prototype Selection to Detect Noise in Imbalanced Classification Data

Francisco Herrera, Chris Cornelis, Nele Verbiest, 2012, IBERAMIA.

A GRASP Algorithm for Clustering

Francisco Herrera, Oscar Cordón, José Ramón Cano, 2002, IBERAMIA.

A Consensus Model for Large-Scale Linguistic Group Decision Making With a Feedback Recommendation Based on Clustered Personalized Individual Semantics and Opposing Consensus Groups

Francisco Herrera, Yucheng Dong, Cong-Cong Li, 2019, IEEE Transactions on Fuzzy Systems.

Editorial: Preference modeling and applications: EUROFUSE 2001

Francisco Herrera, Bernard De Baets, Luis Martínez-López, 2003, Int. J. Intell. Syst..

Multiple Crossover per Couple with Selection of the Two Best Offspring: An Experimental Study with the BLX-alpha Crossover Operator for Real-Coded Genetic Algorithms

Francisco Herrera, Ana M. Sánchez, Elena Pérez, 2002, IBERAMIA.

Gradual distributed real-coded genetic algorithms

Francisco Herrera, Manuel Lozano, F. Herrera, 2000, IEEE Trans. Evol. Comput..

Multi-instance Regression

Francisco Herrera, Chris Cornelis, Sarah Vluymans, 2016 .

Fuzzy Rule Based Classification Systems versus crisp robust learners trained in presence of class noise's effects: A case of study

Francisco Herrera, Julián Luengo, José A. Sáez, 2011, 2011 11th International Conference on Intelligent Systems Design and Applications.

A linear programming method for multiple criteria decision making with probabilistic linguistic information

Francisco Herrera, Zeshui Xu, Huchang Liao, 2017, Inf. Sci..

A group decision making model dealing with comparative linguistic expressions based on hesitant fuzzy linguistic term sets

Francisco Herrera, Luis Martínez-López, Rosa M. Rodríguez, 2013, Inf. Sci..

Evolutionary undersampling for imbalanced big data classification

Francisco Herrera, Chris Cornelis, Sarah Vluymans, 2015, 2015 IEEE Congress on Evolutionary Computation (CEC).

Distinguishing between facts and opinions for sentiment analysis: Survey and challenges

Francisco Herrera, Erik Cambria, Roy E. Welsch, 2018, Inf. Fusion.

Linguistic measures based on fuzzy coincidence for reaching consensus in group decision making

Francisco Herrera, Enrique Herrera-Viedma, José L. Verdegay, 1997, Int. J. Approx. Reason..

A Review of the Application of Multiobjective Evolutionary Fuzzy Systems: Current Status and Further Directions

Francisco Herrera, Hisao Ishibuchi, Rafael Alcalá, 2013, IEEE Transactions on Fuzzy Systems.

2-Tuple Linguistic Decision Based Applications

Francisco Herrera, Luis Martínez, Rosa M. Rodríguez, 2015 .

Consistency of hesitant fuzzy linguistic preference relations: An interval consistency index

Francisco Herrera, Luis Martínez, Yucheng Dong, 2018, Inf. Sci..

Evolutionary Fuzzy Systems: A Case Study in Imbalanced Classification

Francisco Herrera, Alberto Fernández, F. Herrera, 2016, Fuzzy Logic and Information Fusion.

Multiple criteria decision making based on distance and similarity measures under double hierarchy hesitant fuzzy linguistic environment

Francisco Herrera, Zeshui Xu, Huchang Liao, 2018, Comput. Ind. Eng..

Consensus Building With Individual Consistency Control in Group Decision Making

Francisco Herrera, Luis Martínez, Yucheng Dong, 2019, IEEE Transactions on Fuzzy Systems.

A Review on Ensembles for the Class Imbalance Problem: Bagging-, Boosting-, and Hybrid-Based Approaches

Francisco Herrera, Humberto Bustince, Mikel Galar, 2012, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

Designing optimal harmonic filters in power systems using greedy adaptive Differential Evolution

Francisco Herrera, Ning Xiong, Miguel León Ortiz, 2016, 2016 IEEE 21st International Conference on Emerging Technologies and Factory Automation (ETFA).

Balance Dynamic Clustering Analysis and Consensus Reaching Process with Consensus Evolution Networks in Large-scale Group Decision Making

Francisco Herrera, Jindong Qin, Xinwang Liu, 2019 .

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.

TOP25 articles within the journal: Fuzzy Sets and Systems

Francisco Herrera, Luis Magdalena, Oscar Cordón, 2005 .

Editorial Message: Special Issue on Hesitant Fuzzy Linguistic Decision Making: Algorithms, Theory and Applications

Francisco Herrera, Zeshui Xu, Huchang Liao, 2018, International Journal of Fuzzy Systems.

Distributed incremental fingerprint identification with reduced database penetration rate using a hierarchical classification based on feature fusion and selection

Francisco Herrera, Yvan Saeys, Salvador García, 2017, Knowl. Based Syst..

Genetic fuzzy systems: taxonomy, current research trends and prospects

Francisco Herrera, F. Herrera, 2008, Evol. Intell..

A snapshot on nonstandard supervised learning problems: taxonomy, relationships, problem transformations and algorithm adaptations

Francisco Charte, Francisco Herrera, Salvador García, 2018, Progress in Artificial Intelligence.

Evolutionary undersampling for extremely imbalanced big data classification under apache spark

Francisco Herrera, Humberto Bustince, Mikel Galar, 2016, 2016 IEEE Congress on Evolutionary Computation (CEC).

Adaptation-Based Classifiers

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

Memetic algorithms based on local search chains for large scale continuous optimisation problems: MA-SSW-Chains

Francisco Herrera, Ana M. Sánchez, Daniel Molina, 2011, Soft Comput..

SHADE with Iterative Local Search for Large-Scale Global Optimization

Francisco Herrera, Daniel Molina, Antonio LaTorre, 2018, 2018 IEEE Congress on Evolutionary Computation (CEC).

Hesitant Fuzzy Linguistic Term Set and Its Application in Decision Making: A State-of-the-Art Survey

Francisco Herrera, Zeshui Xu, Huchang Liao, 2018, Int. J. Fuzzy Syst..

Addressing Data-Complexity for Imbalanced Data-Sets: A Preliminary Study on the Use of Preprocessing for C4.5

Francisco Herrera, Salvador García, Alberto Fernández, 2009, 2009 Ninth International Conference on Intelligent Systems Design and Applications.

NMC: nearest matrix classification - A new combination model for pruning One-vs-One ensembles by transforming the aggregation problem

Francisco Herrera, Humberto Bustince, Mikel Galar, 2017, Inf. Fusion.

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.

A rational consensus model in group decision making using linguistic assessments

Francisco Herrera, Enrique Herrera-Viedma, José L. Verdegay, 1997, Fuzzy Sets Syst..

Cost-sensitive linguistic fuzzy rule based classification systems under the MapReduce framework for imbalanced big data

Francisco Herrera, José Manuel Benítez, Victoria López, 2015, Fuzzy Sets Syst..

A unifying view on dataset shift in classification

Francisco Herrera, Nitesh V. Chawla, Troy Raeder, 2012, Pattern Recognit..

Big Data, Smart Data and Imbalanced Classification - Preprocessing, Models and Challenges

Francisco Herrera, Francisco Herrera, 2017, CLOSER.

Applications of the linguistic OWA operators in group decision making

Francisco Herrera, Enrique Herrera-Viedma, José L. Verdegay, 1997 .

New trends in the fuzzy modeling part I: novel approaches

Francisco Herrera, Adel M. Alimi, 2006, 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).

A Metahierarchical Rule Decision System to Design Robust Fuzzy Classifiers Based on Data Complexity

Francisco Herrera, José A. Gámez, Alberto Fernández, 2019, IEEE Transactions on Fuzzy Systems.

Fusion of multigranular linguistic information based on the 2-tuple fuzzy linguistic representation model

Francisco Herrera, Enrique Herrera-Viedma, Francisco Chiclana, 2002 .

Special issue: Data mining and hybrid intelligent systems

Francisco Herrera, Fatos Xhafa, Mario Köppen, 2009, Int. J. Hybrid Intell. Syst..

A web tool to support decision making in the housing market using hesitant fuzzy linguistic term sets

Francisco Herrera, Ana M. Sánchez, Rosana Montes-Soldado, 2015, Appl. Soft Comput..

A Tutorial on Distance Metric Learning: Mathematical Foundations, Algorithms and Software pdf

Francisco Herrera, Salvador García, Juan-Luis Suárez, 2018, ArXiv.

A Multiobjective Evolutionary Algorithm for Tuning Fuzzy Rule Based Systems with Measures for Preserving Interpretability

Francisco Herrera, Rafael Alcalá, María José Gacto, 2009, IFSA/EUSFLAT Conf..

A Note on the Estimation of Missing Pairwise Preference Values: a Uninorm Consistency Based Method

Francisco Herrera, Enrique Herrera-Viedma, Sergio Alonso, 2008, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

A first approach for cost-sensitive classification with linguistic Genetic Fuzzy Systems in imbalanced data-sets

Francisco Herrera, Alberto Fernández, Victoria López, 2010, 2010 10th International Conference on Intelligent Systems Design and Applications.

Probabilistic Linguistic MULTIMOORA: A Multicriteria Decision Making Method Based on the Probabilistic Linguistic Expectation Function and the Improved Borda Rule

Francisco Herrera, Zeshui Xu, Huchang Liao, 2018, IEEE Transactions on Fuzzy Systems.

Group decision making with incomplete information.

Francisco Herrera, Enrique Herrera-Viedma, Sergio Alonso, 2005 .

Some issues on consistency of fuzzy preference relations

Francisco Herrera, Enrique Herrera-Viedma, María Luque, 2004, Eur. J. Oper. Res..

Special issue on evolutionary fuzzy systems

Francisco Herrera, Hisao Ishibuchi, Rafael Alcalá, 2011, Int. J. Comput. Intell. Syst..

A position and perspective analysis of hesitant fuzzy sets on information fusion in decision making. Towards high quality progress

Francisco Herrera, Zeshui Xu, Humberto Bustince, 2016, Inf. Fusion.

Implementing algorithms of rough set theory and fuzzy rough set theory in the R package "RoughSets"

Francisco Herrera, Chris Cornelis, Dominik Slezak, 2014, Inf. Sci..

Message from the IEEE TrustCom-ISPA-BigDataSE 2015 general chairs

Francisco Herrera, Valtteri Niemi, Raimo Kantola, 2015, TrustCom 2015.

On the combination of evolutionary algorithms and stratified strategies for training set selection in data mining

Francisco Herrera, José Ramón Cano, Manuel Lozano, 2006, Appl. Soft Comput..

Knowledge Base Learning of Linguistic Fuzzy Rule-Based Systems in a Multi-objective Evolutionary Framework

Francisco Herrera, Rafael Alcalá, Beatrice Lazzerini, 2008, HAIS.

Dynamic Federated Learning Model for Identifying Adversarial Clients pdf

Francisco Herrera, Eugenio Martínez-Cámara, M. Victoria Luzón, 2020, ArXiv.

Design of Experiments in Computational Intelligence: On the Use of Statistical Inference

Francisco Herrera, Salvador García, 2008, HAIS.

On the choice of the best imputation methods for missing values considering three groups of classification methods

Francisco Herrera, Salvador García, Julián Luengo, 2012, Knowledge and Information Systems.

q 2 -Index: Quantitative and Qualitative Evaluation Based on the Number and Impact of Papers in the

Francisco Herrera, Enrique Herrera-Viedma, Sergio Alonso, 2009 .

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

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

On the use of Measures of Separability of Classes to Characterise the Domains of Competence of a Fuzzy Rule Based Classification System

Francisco Herrera, Julián Luengo, F. Herrera, 2009, IFSA/EUSFLAT Conf..

Minutiae-based fingerprint matching decomposition: Methodology for big data frameworks

Francisco Herrera, Salvador García, Daniel Peralta, 2017, Inf. Sci..

A First Study on the Use of Boosting for Class Noise Reparation

Francisco Herrera, Pablo Morales-Alvarez, Julián Luengo, 2016, HAIS.

The minimum cost consensus model considering the implicit trust of opinions similarities in social network group decision‐making

Francisco Herrera, Zaiwu Gong, Huanhuan Zhang, 2019, Int. J. Intell. Syst..

Region-based memetic algorithm with archive for multimodal optimisation

Francisco Herrera, Daniel Molina, Benjamin Lacroix, 2016, Inf. Sci..

Exploring the effectiveness of dynamic ensemble selection in the one-versus-one scheme

Francisco Herrera, Salvador García, Jiafu Tang, 2017, Knowl. Based Syst..

Differential evolution for optimizing the positioning of prototypes in nearest neighbor classification

Francisco Herrera, Salvador García, Isaac Triguero, 2011, Pattern Recognit..

Adaptive genetic operators based on coevolution with fuzzy behaviors

Francisco Herrera, Manuel Lozano, F. Herrera, 2001, IEEE Trans. Evol. Comput..

Ordering-based pruning for improving the performance of ensembles of classifiers in the framework of imbalanced datasets

Francisco Herrera, Humberto Bustince, Mikel Galar, 2016, Inf. Sci..

Instance-Based Classification Methods

Francisco Herrera, Chris Cornelis, Sarah Vluymans, 2016 .

A linguistic decision model for promotion mix management solved with genetic algorithms

Francisco Herrera, Enrique López, Miguel Ángel Rodríguez, 2002, Fuzzy Sets Syst..

Dealing with Noisy Data

Francisco Herrera, Salvador García, Julián Luengo, 2015 .

Applying Linguistic OWA Operators in Consensus Models under Unbalanced Linguistic Information

Francisco Herrera, Enrique Herrera-Viedma, Francisco Javier Cabrerizo, 2011, Recent Developments in the Ordered Weighted Averaging Operators.

Learning with Genetic Algorithms

Francisco Herrera, Luis Magdalena, Oscar Cordón, 2001 .

COR: a methodology to improve ad hoc data-driven linguistic rule learning methods by inducing cooperation among rules

Francisco Herrera, Jorge Casillas, Oscar Cordón, 2002, IEEE Trans. Syst. Man Cybern. Part B.

A fuzzy associative classification system with genetic rule selection for high-dimensional problems

Francisco Herrera, Jesús Alcalá-Fdez, Rafael Alcalá, 2010, 2010 4th International Workshop on Genetic and Evolutionary Fuzzy Systems (GEFS).

On the importance of the validation technique for classification with imbalanced datasets: Addressing covariate shift when data is skewed

Francisco Herrera, Alberto Fernández, Victoria López, 2014, Inf. Sci..

A case study on the application of instance selection techniques for Genetic Fuzzy Rule-Based Classifiers

Francisco Herrera, Rafael Alcalá, Francesco Marcelloni, 2012, 2012 IEEE International Conference on Fuzzy Systems.

Analysis of self‐confidence indices‐based additive consistency for fuzzy preference relations with self‐confidence and its application in group decision making

Yejun Xu, Francisco Herrera, Yucheng Dong, 2019, Int. J. Intell. Syst..

Generating single granularity-based fuzzy classification rules for multiobjective genetic fuzzy rule selection

Francisco Herrera, Hisao Ishibuchi, Rafael Alcalá, 2009, 2009 IEEE International Conference on Fuzzy Systems.

Consensus Model Handling Minority Opinions and Noncooperative Behaviors in Large-Scale Group Decision-Making Under Double Hierarchy Linguistic Preference Relations

Francisco Herrera, Huchang Liao, Zeshui Xu, 2020, IEEE Transactions on Cybernetics.

Score-HeDLiSF: A score function of hesitant fuzzy linguistic term set based on hesitant degrees and linguistic scale functions: An application to unbalanced hesitant fuzzy linguistic MULTIMOORA

Francisco Herrera, Huchang Liao, Arian Hafezalkotob, 2019, Inf. Fusion.

Learning the membership function contexts for mining fuzzy association rules by using genetic algorithms

Francisco Herrera, Jesús Alcalá-Fdez, Rafael Alcalá, 2009, Fuzzy Sets Syst..

An Evolutionary Multiobjective Model and Instance Selection for Support Vector Machines With Pareto-Based Ensembles

Francisco Herrera, Carlos A. Coello Coello, Alejandro Rosales-Pérez, 2017, IEEE Transactions on Evolutionary Computation.

A first study exploring the performance of the state-of-the art CNN model in the problem of breast cancer

Francisco Herrera, Siham Tabik, Boujemâa Achchab, 2018, LOPAL '18.

A Data Mining Software Package Including Data Preparation and Reduction: KEEL

Francisco Herrera, Salvador García, Julián Luengo, 2015 .

Improving the performance of fuzzy rule-based classification systems with interval-valued fuzzy sets and genetic amplitude tuning

Francisco Herrera, Humberto Bustince, Alberto Fernández, 2010, Inf. Sci..

The 2-tuple Linguistic Model: Computing with Words in Decision Making

Francisco Herrera, Rosa M. Rodríguez, Luis Martnez, 2015 .

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.

Designing a compact Genetic fuzzy rule-based system for one-class classification

Francisco Herrera, Ana M. Sánchez, Bartosz Krawczyk, 2014, 2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).

A multi-objective evolutionary method for learning granularities based on fuzzy discretization to improve the accuracy-complexity trade-off of fuzzy rule-based classification systems: D-MOFARC algorithm

Francisco Herrera, Rafael Alcalá, Michela Fazzolari, 2014, Appl. Soft Comput..

Dynamic affinity-based classification of multi-class imbalanced data with one-versus-one decomposition: a fuzzy rough set approach

Francisco Herrera, Chris Cornelis, Sarah Vluymans, 2018, Knowledge and Information Systems.

Linguistic modeling with hierarchical systems of weighted linguistic rules

Francisco Herrera, Rafael Alcalá, Oscar Cordón, 2003, Int. J. Approx. Reason..

SMOTE-GPU: Big Data preprocessing on commodity hardware for imbalanced classification

Francisco Herrera, Miguel Lastra, José Manuel Benítez, 2017, Progress in Artificial Intelligence.

Data Level Preprocessing Methods

Francisco Herrera, Mikel Galar, Salvador García, 2018 .

2-tuple fuzzy linguistic perceptions and probabilistic awareness-based heuristics for modeling consumer purchase behaviors

Francisco Herrera, Jesús Giráldez-Cru, Manuel Chica, 2020, 2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).

Fuzzy Clustering Approach forNon-cooperative Behavior Detection inConsensus Reaching Processes

Francisco Herrera, Luis Martínez, Iván Palomares, 2013 .

A study of the origin and uses of the ordered weighted geometric operator in multicriteria decision making

Francisco Herrera, Enrique Herrera-Viedma, Francisco Chiclana, 2003, Int. J. Intell. Syst..

Applying Memetic algorithm with Improved L-SHADE and Local Search Pool for the 100-digit challenge on Single Objective Numerical Optimization

Francisco Herrera, Daniel Molina, 2019, 2019 IEEE Congress on Evolutionary Computation (CEC).

Distributed Linguistic Representations in Decision Making: Taxonomy, Key Elements and Applications, and Challenges in Data Science and Explainable Artificial Intelligence

Francisco Herrera, Zhen Zhang, Yucheng Dong, 2020, Inf. Fusion.

Tackling the problem of classification with noisy data using Multiple Classifier Systems: Analysis of the performance and robustness

Francisco Herrera, Mikel Galar, Julián Luengo, 2013, Inf. Sci..

Consensus vote models for detecting and filtering neutrality in sentiment analysis

Francisco Herrera, Erik Cambria, M. Victoria Luzón, 2018, Inf. Fusion.

An optimization-based approach to estimate the range of consistency in hesitant fuzzy linguistic preference relations

Francisco Herrera, Luis Martínez, Yucheng Dong, 2016, 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).

A snapshot on nonstandard supervised learning problems: taxonomy, relationships and methods pdf

Francisco Charte, Francisco Herrera, Salvador García, 2018, ArXiv.

Distributed Genetic Tuning of Fuzzy Rule-Based Systems

Francisco Herrera, Rafael Alcalá, José Manuel Benítez, 2009, IFSA/EUSFLAT Conf..

A First Study on the Use of Interval-Valued Fuzzy Sets with Genetic Tuning for Classification with Imbalanced Data-Sets

Francisco Herrera, Humberto Bustince, Alberto Fernández, 2009, HAIS.

Ordinal consensus measure with objective threshold for heterogeneous large-scale group decision making

Ming Tang, Francisco Herrera, Huchang Liao, 2019, Knowl. Based Syst..

A binocular image fusion approach for minimizing false positives in handgun detection with deep learning

Francisco Herrera, Siham Tabik, Roberto Olmos, 2019, Inf. Fusion.

Dynamic and heuristic fuzzy connectives-based crossover operators for controlling the diversity and convergence of real-coded genetic algorithms

Francisco Herrera, José L. Verdegay, Manuel Lozano, 1996, Int. J. Intell. Syst..

Smartdata: Data preprocessing to achieve smart data in R

Francisco Charte, Francisco Herrera, Salvador García, 2019, Neurocomputing.

Deep Learning Hyper-parameter Tuning for Sentiment Analysis in Twitter based on Evolutionary Algorithms

Francisco Herrera, Elena Romero, José Alberto Fernández, 2019, 2019 Federated Conference on Computer Science and Information Systems (FedCSIS).

A note on the internal consistency of various preference representations

Francisco Herrera, Enrique Herrera-Viedma, Francisco Chiclana, 2002, Fuzzy Sets Syst..

Recent advances in genetic fuzzy systems - Guest editorial

Francisco Herrera, Luis Magdalena, Oscar Cordón, 2001, Inf. Sci..

Enhancing Multiclass Classification in FARC-HD Fuzzy Classifier: On the Synergy Between $n$-Dimensional Overlap Functions and Decomposition Strategies

Francisco Herrera, Humberto Bustince, Mikel Galar, 2015, IEEE Transactions on Fuzzy Systems.

A Note on the ITS Topic Evolution in the Period 2000–2009 at T-ITS

Francisco Herrera, Enrique Herrera-Viedma, Antonio Gabriel López-Herrera, 2012, IEEE Transactions on Intelligent Transportation Systems.

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..

Imbalanced Classification with Multiple Classes

Francisco Herrera, Mikel Galar, Salvador García, 2018 .

Statistical computation of feature weighting schemes through data estimation for nearest neighbor classifiers

Francisco Herrera, Joaquín Derrac, Julián Luengo, 2014, Pattern Recognit..

Dynamically updated region based memetic algorithm for the 2013 CEC Special Session and Competition on Real Parameter Single Objective Optimization

Francisco Herrera, Daniel Molina, Benjamin Lacroix, 2013, 2013 IEEE Congress on Evolutionary Computation.

Characterisation of implication operators in fuzzy rule based systems from basic properties

Francisco Herrera, Oscar Cordón, Antonio Peregrín, 1999, EUSFLAT-ESTYLF Joint Conf..

A Consensus Model for Group Decision Making With Incomplete Fuzzy Preference Relations

Francisco Herrera, Enrique Herrera-Viedma, Sergio Alonso, 2007, IEEE Transactions on Fuzzy Systems.

Discrete Optimization A taxonomy and an empirical analysis of multiple objective ant colony optimization algorithms for the bi-criteria TSP q

Francisco Herrera, Oscar Cordón, Carlos García-Martínez, 2007 .

Integrating Continual Personalized Individual Semantics Learning in Consensus Reaching in Linguistic Group Decision Making

Francisco Herrera, Yucheng Dong, Cong-Cong Li, 2022, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

Fuzzy-Citation-KNN: A fuzzy nearest neighbor approach for multi-instance classification

Francisco Herrera, Ana M. Sánchez, Rosana Montes-Soldado, 2016, 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).

Emerging topics and challenges of learning from noisy data in nonstandard classification: a survey beyond binary class noise

Francisco Herrera, Ronaldo C. Prati, Julián Luengo, 2018, Knowledge and Information Systems.

Applicability of the fuzzy operators in the design of fuzzy logic controllers

Francisco Herrera, Oscar Cordón, Antonio Peregrín, 1997, Fuzzy Sets Syst..

Dynamic ensemble selection for multi-class classification with one-class classifiers

Francisco Herrera, Humberto Bustince, Mikel Galar, 2018, Pattern Recognit..

A Multiobjective Evolutionary Approach to Concurrently Learn Rule and Data Bases of Linguistic Fuzzy-Rule-Based Systems

Francisco Herrera, Rafael Alcalá, Beatrice Lazzerini, 2009, IEEE Transactions on Fuzzy Systems.

Influence of fuzzy partition granularity on fuzzy rule-based system behaviour

Francisco Herrera, Oscar Cordón, Pedro Villar, 1999, EUSFLAT-ESTYLF Joint Conf..

Analysis of the Performance of a Semantic Interpretability-Based Tuning and Rule Selection of Fuzzy Rule-Based Systems by Means of a Multi-Objective Evolutionary Algorithm

Francisco Herrera, Rafael Alcalá, María José Gacto, 2010, IEA/AIE.

Algorithm-Level Approaches

Francisco Herrera, Mikel Galar, Salvador García, 2018 .

Memetic Algorithm with Local Search Chaining for Continuous Optimization Problems: A Scalability Test

Francisco Herrera, Daniel Molina, Manuel Lozano, 2009, 2009 Ninth International Conference on Intelligent Systems Design and Applications.

A Survey on Evolutionary Instance Selection and Generation

Francisco Herrera, Salvador García, Joaquín Derrac, 2010, Int. J. Appl. Metaheuristic Comput..

Interpretability of linguistic fuzzy rule-based systems: An overview of interpretability measures

Francisco Herrera, Rafael Alcalá, María José Gacto, 2011, Inf. Sci..

An Insight into Bio-inspired and Evolutionary Algorithms for Global Optimization: Review, Analysis, and Lessons Learnt over a Decade of Competitions

Francisco Herrera, Daniel Molina, Antonio LaTorre, 2018, Cognitive Computation.

Making Decisions on Fuzzy Integer Linear Programming Problems

Francisco Herrera, José L. Verdegay, F. Herrera, 1996 .

Preprocessing Algorithms for Imbalanced Datasets [R package imbalance version 1.0.2.1]

Francisco Herrera, Salvador García, Alberto Fernández, 2020 .

Two-Loop Real-Coded Genetic Algorithms with Adaptive Control of Mutation Step Sizes

Francisco Herrera, Manuel Lozano, F. Herrera, 2000, Applied Intelligence.

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

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

Hybrid crossover operators for real-coded genetic algorithms: an experimental study

Francisco Herrera, Ana M. Sánchez, Manuel Lozano, 2005, Soft Comput..

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.

Decision Making with Unbalanced Linguistic Information

Francisco Herrera, Rosa M. Rodríguez, Luis Martínez, 2015 .

A High Performance Fingerprint Matching System for Large Databases Based on GPU

Francisco Herrera, Miguel Lastra, José Manuel Benítez, 2014, IEEE Transactions on Information Forensics and Security.

WoS query partitioner: A tool to retrieve very large numbers of items from the Web of Science using different source-based partitioning approaches

Francisco Herrera, Enrique Herrera-Viedma, Francisco Javier Cabrerizo, 2010 .

CNC-NOS: Class noise cleaning by ensemble filtering and noise scoring

Francisco Herrera, Abdulrahman H. Altalhi, Saleh Alshomrani, 2018, Knowl. Based Syst..

An overview of ensemble methods for binary classifiers in multi-class problems: Experimental study on one-vs-one and one-vs-all schemes

Francisco Herrera, Humberto Bustince, Mikel Galar, 2011, Pattern Recognit..

Empowering difficult classes with a similarity-based aggregation in multi-class classification problems

Francisco Herrera, Mikel Galar, Edurne Barrenechea Tartas, 2014, Inf. Sci..

A Study on the Evolutionary Adaptive Defuzzification Methods in Fuzzy Modeling

Francisco Herrera, Oscar Cordón, Francisco Alfredo Márquez, 2004, Int. J. Hybrid Intell. Syst..

Learning cooperative linguistic fuzzy rules using the best-worst ant system algorithm

Francisco Herrera, Jorge Casillas, Oscar Cordón, 2005, Int. J. Intell. Syst..

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

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

An Interval Valued K-Nearest Neighbors Classifier

Francisco Herrera, Salvador García, Francisco Chiclana, 2015, IFSA-EUSFLAT.

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..

Linguistic Fuzzy Rules in Data Mining: Follow-Up Mamdani Fuzzy Modeling Principle

Francisco Herrera, Alberto Fernández, F. Herrera, 2012, Combining Experimentation and Theory.

Visualizing Consensus inGroupDecision MakingSituations

Francisco Herrera, Enrique Herrera-Viedma, Francisco Javier Cabrerizo, 2007 .

On Dominance Degrees in Group Decision Making with Linguistic Preferences

Francisco Herrera, Enrique Herrera-Viedma, José L. Verdegay, 1994 .

Connecting the numerical scale model to the unbalanced linguistic term sets

Francisco Herrera, Yucheng Dong, Cong-Cong Li, 2014, 2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).

Choice processes for non-homogeneous group decision making in linguistic setting

Francisco Herrera, Enrique Herrera-Viedma, José L. Verdegay, 1998, Fuzzy Sets Syst..

Editorial: Fuzzy Logic and Artificial Intelligence: A Special Issue on Emerging Techniques and Their Applications

Francisco Herrera, Shun-Feng Su, Fei-Yue Wang, 2020, IEEE Trans. Fuzzy Syst..

Combining Rule Weight Learning and Rule Selection to Obtain Simpler and More Accurate Linguistic Fuzzy Models

Francisco Herrera, Rafael Alcalá, Oscar Cordón, 2003, Modelling with Words.

A Co-evolutionary Framework for Nearest Neighbor Enhancement: Combining Instance and Feature Weighting with Instance Selection

Francisco Herrera, Salvador García, Joaquín Derrac, 2012, HAIS.

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..

Inconsistencies on TripAdvisor reviews: A unified index between users and Sentiment Analysis Methods

Francisco Herrera, Luigi Troiano, Erik Cambria, 2019, Neurocomputing.

A Historical Account of Types of Fuzzy Sets and Their Relationships

Francisco Herrera, Zeshui Xu, Hani Hagras, 2016, IEEE Transactions on Fuzzy Systems.

Data Preprocessing in Data Mining

Francisco Herrera, Salvador García, Julián Luengo, 2014, Intelligent Systems Reference Library.

Ten years of genetic fuzzy systems: current framework and new trends

Francisco Herrera, Luis Magdalena, Oscar Cordón, 2004, Fuzzy Sets Syst..

Revisiting Fuzzy and Linguistic Decision Making: Scenarios and Challenges for Making Wiser Decisions in a Better Way

Francisco Herrera, Enrique Herrera-Viedma, Francisco Javier Cabrerizo, 2021, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

Tackling Multilabel Imbalance through Label Decoupling and Data Resampling Hybridization

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

Hesitant Fuzzy Sets: An Emerging Tool in Decision Making

Francisco Herrera, Luis Martínez-López, Zeshui Xu, 2014, Int. J. Intell. Syst..

Genetic Fuzzy Systems - Evolutionary Tuning and Learning of Fuzzy Knowledge Bases

Francisco Herrera, Luis Magdalena, Oscar Cordón, 2002, Advances in Fuzzy Systems - Applications and Theory.

A two-step communication opinion dynamics model with self-persistence and influence index for social networks based on the DeGroot model

Francisco Herrera, Abdulrahman H. Altalhi, Zhibin Wu, 2020, Inf. Sci..

From Big Data to Smart Data with the K-Nearest Neighbours Algorithm

Francisco Herrera, Salvador García, Julián Luengo, 2016, 2016 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData).

Managing Borderline and Noisy Examples in Imbalanced Classification by Combining SMOTE with Ensemble Filtering

Francisco Herrera, Jerzy Stefanowski, Julián Luengo, 2014, IDEAL.

Hesitant Fuzzy Linguistic Term Sets

Francisco Herrera, Rosa M. Rodríguez, Luis Martínez, 2011 .

What do people think about this monument? Understanding negative reviews via deep learning, clustering and descriptive rules

Francisco Herrera, Erik Cambria, Yew-Soon Ong, 2020, J. Ambient Intell. Humaniz. Comput..

Aggregation operators for linguistic weighted information

Francisco Herrera, Enrique Herrera-Viedma, F. Herrera, 1997, IEEE Trans. Syst. Man Cybern. Part A.

A comparison on scalability for batch big data processing on Apache Spark and Apache Flink

Francisco Herrera, Sergio Ramírez-Gallego, Salvador García, 2017 .

On the use of convolutional neural networks for robust classification of multiple fingerprint captures

Francisco Herrera, Yvan Saeys, Salvador García, 2017, Int. J. Intell. Syst..

Surveying alignment-free features for Ortholog detection in related yeast proteomes by using supervised big data classifiers

Francisco Herrera, Reinaldo Molina Ruiz, Guillermin Agüero-Chapin, 2018, BMC Bioinformatics.

Fuzzy boolean programming problems with fuzzy costs: A general study

Francisco Herrera, José L. Verdegay, F. Herrera, 1996, Fuzzy Sets Syst..

On the Combination of Pairwise and Granularity Learning for Improving Fuzzy Rule-Based Classification Systems: GL-FARCHD-OVO

Francisco Herrera, Alberto Fernández, Pedro Villar, 2015, CORES.

Dynamic classifier selection for One-vs-One strategy: Avoiding non-competent classifiers

Francisco Herrera, Humberto Bustince, Mikel Galar, 2013, Pattern Recognit..

Managing Monotonicity in Classification by a Pruned AdaBoost

Francisco Herrera, Salvador García, Sergio González, 2016, HAIS.

An optimization-based approach to adjusting unbalanced linguistic preference relations to obtain a required consistency level

Francisco Herrera, Yucheng Dong, Cong-Cong Li, 2015, Inf. Sci..

Introduction: Genetic fuzzy systems

Francisco Herrera, Luis Magdalena, F. Herrera, 1998, Int. J. Intell. Syst..

Cognitive Computing: Human-Centered Computing with Cognitive Intelligence on Clouds

Francisco Herrera, Min Chen, Kai Hwang, 2018 .

7th International Conference on Knowledge Management in Organizations: Service and Cloud Computing, KMO 2012, Salamanca, Spain, 11-13 July, 2012

Francisco Herrera, Lorna Uden, Juan Manuel Corchado Rodríguez, 2013, KMO.

A tour on big data classification: Selected Computational Intelligence approaches

Francisco Herrera, 2015, IFSA-EUSFLAT.

On the use of MapReduce for imbalanced big data using Random Forest

Francisco Herrera, José Manuel Benítez, Victoria López, 2014, Inf. Sci..

Detection of Fir Trees (Abies sibirica) Damaged by the Bark Beetle in Unmanned Aerial Vehicle Images with Deep Learning

Francisco Herrera, Siham Tabik, Domingo Alcaraz-Segura, 2019, Remote. Sens..

A survey of fingerprint classification Part I: Taxonomies on feature extraction methods and learning models

Francisco Herrera, Humberto Bustince, Carlos Lopez-Molina, 2015, Knowl. Based Syst..

Improving a fuzzy association rule-based classification model by granularity learning based on heuristic measures over multiple granularities

Francisco Herrera, Hisao Ishibuchi, Rafael Alcalá, 2013, 2013 IEEE International Workshop on Genetic and Evolutionary Fuzzy Systems (GEFS).

Guest Editorial: Computational Intelligence for Big Data Analytics

Francisco Herrera, Mikel Galar, Alberto Fernández, 2019, Cognitive Computation.

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.

IPADE: Iterative Prototype Adjustment for Nearest Neighbor Classification

Francisco Herrera, Salvador García, Isaac Triguero, 2010, IEEE Transactions on Neural Networks.

Fuzzy rough classifiers for class imbalanced multi-instance data

Francisco Herrera, Chris Cornelis, Sarah Vluymans, 2016, Pattern Recognit..

Integrating a differential evolution feature weighting scheme into prototype generation

Francisco Herrera, Salvador García, Joaquín Derrac, 2012, Neurocomputing.

Sparse Representation-Based Intuitionistic Fuzzy Clustering Approach to Find the Group Intra-Relations and Group Leaders for Large-Scale Decision Making

Francisco Herrera, Ru-Xi Ding, Kun Shang, 2019, IEEE Transactions on Fuzzy Systems.

Increasing fuzzy rules cooperation based on evolutionary adaptive inference systems: Research Articles

Francisco Herrera, Jesús Alcalá-Fdez, Francisco Alfredo Márquez, 2007 .

A study of the scaling up capabilities of stratified prototype generation

Francisco Herrera, Salvador García, Joaquín Derrac, 2011, 2011 Third World Congress on Nature and Biologically Inspired Computing.

Predicting noise filtering efficacy with data complexity measures for nearest neighbor classification

Francisco Herrera, Julián Luengo, José A. Sáez, 2013, Pattern Recognit..

Monotonic Random Forest with an Ensemble Pruning Mechanism based on the Degree of Monotonicity

Francisco Herrera, Salvador García, Sergio González, 2015, New Generation Computing.

An Overview of E-Learning in Cloud Computing

Francisco Herrera, Daniel Peralta, José Manuel Benítez, 2012 .

Guest Editors' Introduction

Francisco Herrera, Francesco Marcelloni, Vincenzo Loia, 2008, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

Fuzzy modeling by hierarchically built fuzzy rule bases

Francisco Herrera, Oscar Cordón, Igor Zwir, 2001, Int. J. Approx. Reason..

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..

Enhancing the effectiveness and interpretability of decision tree and rule induction classifiers with evolutionary training set selection over imbalanced problems

Francisco Herrera, Salvador García, Alberto Fernández, 2009, Appl. Soft Comput..

A Review of Distributed Data Models for Learning

Francisco Herrera, Alberto Fernández, Antonio Peregrín, 2017, HAIS.

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..

Unsupervised Multiple Instance Learning

Francisco Herrera, Chris Cornelis, Sarah Vluymans, 2016 .

A Three-Stage Method for Designing Genetic Fuzzy Systems by Learning from Examples

Francisco Herrera, Oscar Cordón, Manuel Lozano, 1996, PPSN.

Un estudio empírico preliminar sobre los tests estadísticos más habituales en el aprendizaje automático

Francisco Herrera, Luciano Sánchez, José Otero, 2004 .

Using the One-vs-One decomposition to improve the performance of class noise filters via an aggregation strategy in multi-class classification problems

Francisco Herrera, André Carlos Ponce de Leon Ferreira de Carvalho, Ana Carolina Lorena, 2015, Knowl. Based Syst..

Imbalance: Oversampling algorithms for imbalanced classification in R

Francisco Herrera, Salvador García, Alberto Fernández, 2018, Knowl. Based 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).

Deep Learning in Video Multi-Object Tracking: A Survey

Francisco Herrera, Luigi Troiano, Roberto Tagliaferri, 2019, Neurocomputing.

Searching for basic properties obtaining robust implication operators in fuzzy control

Francisco Herrera, Oscar Cordón, Antonio Peregrín, 2000, Fuzzy Sets Syst..

Optimising real parameters using the information of a mesh of solutions: VMO algorithm

Francisco Herrera, Rafael Bello, Daniel Molina, 2012, 2012 IEEE Congress on Evolutionary Computation.

2-Tuple Linguistic Model

Francisco Herrera, Rosa M. Rodríguez, Luis Martínez, 2015 .

Incorporating Knowledge in Evolutionary Prototype Selection

Francisco Herrera, José Ramón Cano, Salvador García, 2006, IDEAL.

Social network analysis-based conflict relationship investigation and conflict degree-based consensus reaching process for large scale decision making using sparse representation

Francisco Herrera, Xueqing Wang, Ru-Xi Ding, 2019, Inf. Fusion.

A Two-stage Evolutionary Process for Designing Tsk Fuzzy Rule-based Systems a Two-stage Evolutionary Process for Designing Tsk Fuzzy Rule-based Systems

Francisco Herrera, Oscar Cordón, F. Herrera, 1996 .

An insight into imbalanced Big Data classification: outcomes and challenges

Francisco Herrera, Nitesh V. Chawla, Alberto Fernández, 2017 .

Editorial Real coded genetic algorithms

Francisco Herrera, Manuel Lozano, F. Herrera, 2005, Soft Comput..

Hierarchical distributed genetic algorithms

Francisco Herrera, Claudio Moraga, Manuel Lozano, 1999 .

CURIE: a cellular automaton for concept drift detection pdf

Francisco Herrera, Javier Del Ser, Eneko Osaba, 2020, Data Mining and Knowledge Discovery.

FINDING FUZZY IDENTIFICATION SYSTEM PARAMETERS USING A NEW DYNAMIC MIGRATION PERIOD-BASED DISTRIBUTED GENETIC ALGORITHM

Francisco Herrera, Marco Antonio Castro, 2009 .

Why Linguistic Fuzzy Rule Based Classification Systems perform well in Big Data Applications?

Francisco Herrera, Abdulrahman H. Altalhi, Alberto Fernández, 2017, Int. J. Comput. Intell. Syst..

A Proposal of Evolutionary Prototype Selection for Class Imbalance Problems

Francisco Herrera, José Ramón Cano, Salvador García, 2006, IDEAL.

Consensus reaching in social network DeGroot Model: The roles of the Self-confidence and node degree

Francisco Herrera, Yucheng Dong, Xia Chen, 2019, Inf. Sci..

Automatic whale counting in satellite images with deep learning

Francisco Herrera, Siham Tabik, Emilio Guirado, 2018, bioRxiv.

Knowledge‐based systems and fuzzy boolean programming

Francisco Herrera, José L. Verdegay, Juan Luis Castro, 1994, Int. J. Intell. Syst..

Feature Selection and Granularity Learning in Genetic Fuzzy Rule-Based Classification Systems for Highly Imbalanced Data-Sets

Francisco Herrera, Alberto Fernández, Ramón Alberto Carrasco, 2012, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

Fuzzy adaptive genetic algorithms: design, taxonomy, and future directions

Francisco Herrera, Manuel Lozano, F. Herrera, 2003, Soft Comput..

Multiobjective genetic fuzzy rule selection of single granularity-based fuzzy classification rules and its interaction with the lateral tuning of membership functions

Francisco Herrera, Hisao Ishibuchi, Rafael Alcalá, 2011, Soft Comput..

A study on the use of imputation methods for experimentation with Radial Basis Function Network classifiers handling missing attribute values: The good synergy between RBFNs and EventCovering method

Francisco Herrera, Salvador García, Julián Luengo, 2010, Neural Networks.

A linguistic hierarchical evaluation model for engineering systems

Francisco Herrera, Jian-Bo Yang, Jun Liu, 2006 .

Eliciting comparative linguistic expressions in group decision making

Francisco Herrera, Luis Martínez-López, Rosa M. Rodríguez, 2013, 2013 Joint IFSA World Congress and NAFIPS Annual Meeting (IFSA/NAFIPS).

Fuzzy nearest neighbor algorithms: Taxonomy, experimental analysis and prospects

Francisco Herrera, Salvador García, Joaquín Derrac, 2014, Inf. Sci..

Group decision making with incomplete fuzzy linguistic preference relations

Francisco Herrera, Enrique Herrera-Viedma, Francisco Javier Cabrerizo, 2009, Int. J. 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 CLASSIFIED REVIEW ON THE COMBINATION FUZZY LOGIC–GENETIC ALGORITHMS BIBLIOGRAPHY: 1989–1995

Francisco Herrera, Manuel Lozano, Oscar Cordón, 1997 .

Genetic tuning on fuzzy systems based on the linguistic 2-tuples representation

Francisco Herrera, Rafael Alcalá, F. Herrera, 2004, 2004 IEEE International Conference on Fuzzy Systems (IEEE Cat. No.04CH37542).

On the Use of Distributed Genetic Algorithms for the Tuning of Fuzzy Rule Based-Systems

Francisco Herrera, Rafael Alcalá, José Manuel Benítez, 2010, Parallel and Distributed Computational Intelligence.

A linguistic hierarchical decision making model for evaluating engineering systems

Francisco Herrera, Jian-Bo Yang, Jun Liu, 2004 .

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.

Revisiting crowd behaviour analysis through deep learning: Taxonomy, anomaly detection, crowd emotions, datasets, opportunities and prospects

Francisco Herrera, Isabelle Hupont, Siham Tabik, 2020, Information Fusion.

Editors’ Preface

Francisco Herrera, Cesar Analide, 2012, Progress in Artificial Intelligence.

Using evolutionary algorithms as instance selection for data reduction in KDD: an experimental study

Francisco Herrera, José Ramón Cano, Manuel Lozano, 2003, IEEE Trans. Evol. Comput..

Integrating multiplicative preference relations in a multipurpose decision-making model based on fuzzy preference relations

Francisco Herrera, Enrique Herrera-Viedma, Francisco Chiclana, 2001, Fuzzy Sets Syst..

Analyzing the presence of noise in multi-class problems: alleviating its influence with the One-vs-One decomposition

Francisco Herrera, Mikel Galar, Julián Luengo, 2012, Knowledge and Information Systems.

Guest Editorial: Recent Trends in Intelligent Systems

Francisco Herrera, Jose Miguel Puerta, José A. Gámez, 2017, Int. J. Intell. Syst..

Enhancing IPADE Algorithm with a Different Individual Codification

Francisco Herrera, Salvador García, Isaac Triguero, 2011, HAIS.

Evolutionary fuzzy k-nearest neighbors algorithm using interval-valued fuzzy sets

Francisco Herrera, Salvador García, Francisco Chiclana, 2016, Inf. Sci..

Virtual learning environment to predict withdrawal by leveraging deep learning

Francisco Herrera, Sebastián Ventura, Saeed-Ul Hassan, 2019, Int. J. Intell. Syst..

Hybrid Distributed Real-Coded Genetic Algorithms

Francisco Herrera, Claudio Moraga, Manuel Lozano, 1998, PPSN.

A case study on medical diagnosis of cardiovascular diseases using a Genetic Algorithm for Tuning Fuzzy Rule-Based Classification Systems with Interval-Valued Fuzzy Sets

Francisco Herrera, Humberto Bustince, Miguel Pagola, 2011, 2011 IEEE Symposium on Advances in Type-2 Fuzzy Logic Systems (T2FUZZ).

HFER: Promoting Explainability in Fuzzy Systems via Hierarchical Fuzzy Exception Rules

Francisco Herrera, Alberto Fernandez, José Ramón Trillo, 2020, 2020 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).

Revisiting inconsistent judgments for incomplete fuzzy linguistic preference relations: Algorithms to identify and rectify ordinal inconsistencies

Yejun Xu, Francisco Herrera, Feng Ma, 2019, Knowl. Based Syst..

SEG-SSC: A Framework Based on Synthetic Examples Generation for Self-Labeled Semi-Supervised Classification

Francisco Herrera, Salvador García, Isaac Triguero, 2015, IEEE Transactions on Cybernetics.

An automatic extraction method of the domains of competence for learning classifiers using data complexity measures

Francisco Herrera, Julián Luengo, J. Luengo, 2013, Knowledge and Information Systems.

Addressing covariate shift for Genetic Fuzzy Systems classifiers: A case of study with FARC-HD for imbalanced datasets

Francisco Herrera, Alberto Fernández, Victoria López, 2013, 2013 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).

A New Hesitant Fuzzy Linguistic ORESTE Method for Hybrid Multicriteria Decision Making

Francisco Herrera, Huchang Liao, Jiuping Xu, 2018, IEEE Transactions on Fuzzy Systems.

Shared domains of competence of approximate learning models using measures of separability of classes

Francisco Herrera, Julián Luengo, F. Herrera, 2012, Inf. Sci..

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.

A First Approach in Evolutionary Fuzzy Systems based on the lateral tuning of the linguistic labels for Big Data classification

Francisco Herrera, Alberto Fernández, Sara del Río, 2016, 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).

Mining association rules on Big Data through MapReduce genetic programming

Francisco Herrera, Sebastián Ventura, José María Luna, 2017, Integr. Comput. Aided Eng..

CONSISTENCY OF HESITANT FUZZY PREFERENCE RELATIONS

Yejun Xu, Francisco Herrera, Rosa M. Rodríguez, 2016 .

Multiple Instance Learning

Francisco Herrera, Chris Cornelis, Sarah Vluymans, 2016, Springer International Publishing.

A first attempt on global evolutionary undersampling for imbalanced big data

Francisco Herrera, Humberto Bustince, Mikel Galar, 2017, 2017 IEEE Congress on Evolutionary Computation (CEC).

Connecting the linguistic hierarchy and the numerical scale for the 2-tuple linguistic model and its use to deal with hesitant unbalanced linguistic information

Francisco Herrera, Yucheng Dong, Cong-Cong Li, 2016, Inf. Sci..

Subgroup Discovery with Linguistic Rules

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

Solving multi-class problems with linguistic fuzzy rule based classification systems based on pairwise learning and preference relations

Francisco Herrera, Humberto Bustince, Edurne Barrenechea Tartas, 2010, Fuzzy Sets Syst..

Exact fuzzy k-nearest neighbor classification for big datasets

Francisco Herrera, Salvador García, Julián Luengo, 2017, 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE).

Software and Libraries for Imbalanced Classification

Francisco Herrera, Mikel Galar, Salvador García, 2018 .

GPU-SME-kNN: Scalable and memory efficient kNN and lazy learning using GPUs

Francisco Herrera, Miguel Lastra, Jaume Bacardit, 2016, Inf. Sci..

Hybridizing Hierarchical and Weighted Linguistic Rules

Francisco Herrera, Rafael Alcalá, Jorge Casillas, 2002, SAC '02.

A proposal for improving the accuracy of linguistic modeling

Francisco Herrera, Oscar Cordón, F. Herrera, 2000, IEEE Trans. Fuzzy Syst..

BELIEF: A distance-based redundancy-proof feature selection method for Big Data pdf

Francisco Herrera, Salvador García, Sergio Ramírez-Gallego, 2018, Inf. Sci..

Direct approach processes in group decision making using linguistic OWA operators

Francisco Herrera, Enrique Herrera-Viedma, José L. Verdegay, 1996, Fuzzy Sets Syst..

A genetic rule weighting and selection process for fuzzy control of heating, ventilating and air conditioning systems

Francisco Herrera, Rafael Alcalá, Jorge Casillas, 2005, Eng. Appl. Artif. Intell..

Evolutionary-based selection of generalized instances for imbalanced classification

Francisco Herrera, Salvador García, Cristóbal J. Carmona, 2012, Knowl. Based Syst..

Deep Learning in Omics Data Analysis and Precision Medicine

Francisco Herrera, Siham Tabik, Igor Zwir, 2019, Computational Biology.

An extraction method for the characterization of the Fuzzy Rule Based Classification Systems' behavior using data complexity measures: A case of study with FH-GBML

Francisco Herrera, Julián Luengo, F. Herrera, 2010, International Conference on Fuzzy Systems.

SMOTE-IPF: Addressing the noisy and borderline examples problem in imbalanced classification by a re-sampling method with filtering

Francisco Herrera, Jerzy Stefanowski, Julián Luengo, 2015, Inf. Sci..

Analysis of new niching genetic algorithms for finding multiple solutions in the job shop scheduling

Francisco Herrera, Elena Pérez, Marta Posada, 2012, J. Intell. Manuf..

Group decision making with double hierarchy hesitant fuzzy linguistic preference relations: Consistency based measures, index and repairing algorithms and decision model

Francisco Herrera, Zeshui Xu, Huchang Liao, 2019, Inf. Sci..

A memetic algorithm for evolutionary prototype selection: A scaling up approach

Francisco Herrera, José Ramón Cano, Salvador García, 2008, Pattern Recognit..

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.

Adaptive local search parameters for real-coded memetic algorithms

Francisco Herrera, Daniel Molina, Manuel Lozano, 2005, 2005 IEEE Congress on Evolutionary Computation.

MonuMAI: Dataset, deep learning pipeline and citizen science based app for monumental heritage taxonomy and classification

Francisco Herrera, Siham Tabik, Rosana Montes-Soldado, 2021, Neurocomputing.

Decision Making in Heterogeneous Context: 2-Tuple Linguistic Based Approaches

Francisco Herrera, Rosa M. Rodríguez, Luis Martínez, 2015 .

Multi-instance Classification

Francisco Herrera, Chris Cornelis, Sarah Vluymans, 2016 .

A distance-based framework to deal with ordinal and additive inconsistencies for fuzzy reciprocal preference relations

Yejun Xu, Francisco Herrera, Huimin Wang, 2016, Inf. Sci..

Guest Editorial - Computing with Words: Foundations and Applications

Francisco Herrera, Enrique Herrera-Viedma, F. Herrera, 2001, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

A hierarchical knowledge-based environment for linguistic modeling: models and iterative methodology

Francisco Herrera, Oscar Cordón, Igor Zwir, 2003, Fuzzy Sets Syst..

A Study on the Use of Statistical Tests for Experimentation with Neural Networks

Francisco Herrera, Salvador García, Julián Luengo, 2007, IWANN.

Defective alternatives detection-based multi-attribute intuitionistic fuzzy large-scale decision making model

Francisco Herrera, Ru-Xi Ding, Qi Zhou, 2019, Knowl. Based Syst..

Study of the Influence of the Local Search Method in Memetic Algorithms for Large Scale Continuous Optimization Problems

Francisco Herrera, Daniel Molina, Manuel Lozano, 2009, LION.

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..

Sentiment Analysis in TripAdvisor

Francisco Herrera, M. Victoria Luzón, Ana Valdivia, 2017, IEEE Intelligent Systems.

A Multiobjective Genetic Algorithm for Feature Selection and Data Base Learning in Fuzzy-Rule Based Classification Systems

Francisco Herrera, Luis Magdalena, Oscar Cordón, 2003 .

A survey on fingerprint minutiae-based local matching for verification and identification: Taxonomy and experimental evaluation

Francisco Herrera, Humberto Bustince, Mikel Galar, 2015, Inf. Sci..

Asynchronous Processing for Latent Fingerprint Identification on Heterogeneous CPU-GPU Systems

Francisco Herrera, Yvan Saeys, Siham Tabik, 2020, IEEE Access.

Increasing fuzzy rules cooperation based on evolutionary adaptive inference systems

Francisco Herrera, Jesús Alcalá-Fdez, Francisco Alfredo Márquez, 2007, Int. J. Intell. Syst..

Improving Pairwise Learning Classification in Fuzzy Rule Based Classification Systems Using Dynamic Classifier Selection

Francisco Herrera, Humberto Bustince, Mikel Galar, 2015, IFSA-EUSFLAT.

Ordinal regression with explainable distance metric learning based on ordered sequences

Francisco Herrera, Salvador García, Juan Luis Suárez, 2021, Mach. Learn..

Consensus Reaching and Strategic Manipulation in Group Decision Making With Trust Relationships

Francisco Herrera, Yucheng Dong, Hengjie Zhang, 2020, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

A consensus process based on regret theory with probabilistic linguistic term sets and its application in venture capital

Francisco Herrera, Zeshui Xu, Xiaoli Tian, 2021, Inf. Sci..

Multiple instance classification: Bag noise filtering for negative instance noise cleaning

Francisco Herrera, Ronaldo C. Prati, Julián Luengo, 2021, Inf. Sci..

A Practical Tutorial for Decision Tree Induction

Francisco Herrera, Víctor Adrián Sosa-Hernández, Octavio Loyola-González, 2021, ACM Comput. Surv..

Francisco Herrera, Enrique Herrera-Viedma, Cristina Zuheros, 2021, Inf. Fusion.

An interval type-2 fuzzy Kano-prospect-TOPSIS based QFD model: Application to Chinese e-commerce service design

Francisco Herrera, Tong Wu, Xinwang Liu, 2021, Appl. Soft Comput..

Measuring volatility based on ordered weighted average operators: The case of agricultural product prices

Francisco Herrera, José M. Merigó, Enrique Herrera-Viedma, 2021, Fuzzy Sets Syst..

On the Usefulness of Fuzzy Rule Based Systems Based on Hierarchical Linguistic Fuzzy Partitions

Francisco Herrera, Alberto Fernández, María José del Jesus, 2011 .

Special issue on "New Trends in Data Mining" NTDM

Francisco Herrera, Francisco Herrera, Nicolás García-Pedrajas, 2012, Knowl. Based Syst..

Prototype Selection for Nearest Neighbor Classification : Survey of Methods

Francisco Herrera, José Ramón Cano, S. García, 2010 .

Approaching Fuzzy Integer Linear Programming Problems

Francisco Herrera, José L. Verdegay, F. Herrera, 1991 .

Consistency properties for preference relations: T-additive and T-multiplicative transitivity

Francisco Herrera, Enrique Herrera-Viedma, Francisco Chiclana, 2004 .

COR Methodology: A Simple Way to Obtain Linguistic Fuzzy Models with Good Interpretability and Accuracy

Francisco Herrera, Jorge Casillas, Oscar Cordón, 2003 .

CONSENSUS BASED ON MULTIPLICATIVE CONSISTENT DOUBLE HIERARCHY LINGUISTIC PREFERENCES: VENTURE CAPITAL IN REAL ESTATE MARKET

Francisco Herrera, Zeshui Xu, Huchang Liao, 2019, International Journal of Strategic Property Management.

Different Proposals to Improve the Accuracy of Fuzzy Linguistic Modeling

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

An Effective Big Data Supervised Imbalanced Classification Approach for Ortholog Detection in Related Yeast Species

Francisco Herrera, Guillermin Agüero-Chapin, Deborah Galpert, 2015, BioMed research international.

Representation models for aggregating linguistic information: issues and analysis

Francisco Herrera, Luis Martínez, Enrique Herrera-Viedma, 2002 .

SMOTE-RS B ∗ : a hybrid preprocessing approach based on oversampling and undersampling for high imbalanced datasets using SMOTE and rough sets theory

Francisco Herrera, Rafael Bello, Enislay Ramentol, 2022 .

Additive consistency of fuzzy preference relations: characterization and construction.

Francisco Herrera, Enrique Herrera-Viedma, Francisco Chiclana, 2003 .

Applying Genetic Algorithms in Fuzzy Optimization Problems

Francisco Herrera, José L. Verdegay, Manuel Lozano, 1994 .

Solving linear Boolean programming problems with imprecise costs

Francisco Herrera, José L. Verdegay, Juan Castro, 1992, [1992 Proceedings] IEEE International Conference on Fuzzy Systems.

A New ACO Model Integrating Evolutionary Computation Concepts: The Best-Worst Ant System

Francisco Herrera, Oscar Cordón, Francisco Herrera, 2000 .

Encouraging Cooperation in the Genetic Iterative Rule Learning Approach for Qualitative Modeling

Francisco Herrera, Oscar Cordón, Antonio González, 1999 .

Using different transitivity properties to deal with incomplete fuzzy preference relations in group decision making environments

Francisco Herrera, Enrique Herrera-Viedma, Sergio Alonso, 2008 .

Learning and Tuning Fuzzy Rule-Based Systems for Linguistic Modeling

Francisco Herrera, Rafael Alcalá, Jorge Casillas, 2000 .

A decision aid system to provide consistent linguistic preference relations.

Francisco Herrera, Enrique Herrera-Viedma, Francisco Javier Cabrerizo, 2006 .

Boolean programming problems with fuzzy constraints

Francisco Herrera, Hans-Jürgen Zimmermann, José L. Verdegay, 1993 .

A Tutorial on Distance Metric Learning: Mathematical Foundations, Algorithms and Experiments

Francisco Herrera, Salvador García, Juan Luis Suárez, 2018 .

Aggregation schemes for binarization techniques . Methods ’ description

Francisco Herrera, Humberto Bustince, Mikel Galar, 2010 .

Different approaches to induce cooperation in fuzzy linguistic models under the COR methodology

Francisco Herrera, Jorge Casillas, Oscar Cordón, 2002 .