Publications

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2018
A Pareto Based Ensemble with Feature and Instance Selection for Learning from Multi-Class Imbalanced Datasets, Fernández, A., Carmona C. J., del Jesus M.J., and Herrera F. , Proc. of the XVIII Conferencia de la Asociación Española para la Inteligencia Artificial (XVIII CAEPIA), p.1316-1317, (2018) PDF icon 2018 - CAEPIA-262.pdf (63.54 KB)
A Unifying Analysis for the Supervised Descriptive Rule Discovery via the Weighted Relative Accuracy, Carmona, C. J., del Jesus M. J., and Herrera F. , Knowledge-Based Systems, Volume 139, p.89-100, (2018) PDF icon 2018-Carmona-KBS.pdf (1.57 MB)
Atipicidad: Medida de calidad clave dentro del descubrimiento de reglas descriptivas supervisadas, Carmona, C. J., del Jesus M.J., and Herrera F. , Proc. of the XVIII Conferencia de la Asociación Española para la Inteligencia Artificial (XVIII CAEPIA), p.827-828, (2018) PDF icon 2018 - CAEPIA-70.pdf (67.19 KB)
2016
A View on Fuzzy Systems for Big Data: Progress and Opportunities, Fernández, A., Carmona C. J., del Jesus M. J., and Herrera F. , International Journal of Computational Intelligence Systems, Volume 9, Number 1, p.69-80, (2016) PDF icon 2016-Fernandez-IJCIS.pdf (455.58 KB)
2015
Addressing imbalance in multilabel classification: Measures and random resampling algorithms, Charte, F., Rivera-Rivas A. J., del Jesus M. J., and Herrera F. , Neurocomputing, Volume 163, p.3–16, (2015)
Resampling Multilabel Datasets by Decoupling Highly Imbalanced Labels, Charte, F., Rivera-Rivas A. J., del Jesus M. J., and Herrera F. , Proceedings of 10th International Conference on Hybrid Artificial Intelligence Systems (HAIS 2015), June, Volume 9121, Bilbao (Spain), p.489–501, (2015)
2012
A Multi-Objective Evolutionary Algorithm for an Effective Tuning of Fuzzy Logic Controllers in Heating, Ventilating and Air Conditioning Systems, Gacto, M. J., Alcalá R., and Herrera F. , Applied Intelligence, Volume 36, Number 2, p.330-347, (2012)
A Preliminary Study on Selecting the Optimal Cut Points in Discretization by Evolutionary Algorithms, García, S., López V., Luengo J., Carmona C. J., and Herrera F. , 1st International Conference on Pattern Recognition Applications and Methods (ICPRAM), February, Villamoura - (Portugal), p.211-216, (2012) PDF icon 2012 - ICPRAM.pdf (106.28 KB)
A Review on Ensembles for Class Imbalance Problem: Bagging, Boosting and Hybrid Based Approaches, Galar, M., Fernández A., Barrenechea E., Bustince H., and Herrera F. , IEEE Transactions on System, Man and Cybernetics - Part C: Applications and Reviews, Volume 42, Number 4, p.463-484, (2012)
Analysis of preprocessing vs. cost-sensitive learning for imbalanced classification. Open problems on intrinsic data characteristics, López, V., Fernández A., Moreno-Torres J.G., and Herrera F. , Expert Systems with Applications, Volume 39, Number 7, p.6585-6608, (2012)
Aprendizaje Evolutivo De Sistemas Aproximativos De Tipo TSK Para Problemas De Alta Dimensionalidad, Gacto, M. J., Alcalá R., and Herrera F. , XVI Congreso Español sobre Tecnologías y Lógica Fuzzy (ESTYLF), February, Valladolid (Spain), p.295-300, (2012)
Evolutionary-Based Selection of Generalized Instances for Imbalanced Classification, García, S., Derrac J., Triguero I., Carmona C. J., and Herrera F. , Knowledge-Based Systems, Volume 25, Number 1, p.3-12, (2012) PDF icon 2012-Garcia-KBS.pdf (522.95 KB)
Feature Selection and Granularity Learning in Genetic Fuzzy Rule-Based Classication Systems for Highly Imbalanced Data-Sets, Villar, P., Fernández A., Carrasco R., and Herrera F. , International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, Volume 20, Number 3, p.369-397, (2012)
Improving Multi-label Classifiers via Label Reduction with Association Rules, Charte, F., Rivera-Rivas A. J., del Jesus M. J., and Herrera F. , 7th International Conference (HAIS), March, Volume II, Salamanca (Spain), p.188-199, (2012)
Prototype Selection for Nearest Neighbor Classification: Taxonomy and Empirical Study, García, S., Derrac Joaquín, Cano J. R., and Herrera F. , IEEE Transactions Pattern Analysis and Machiche Intelligence, Volume 34, Number 3, p.417–435, (2012)
Replacement Strategies to Preserve Useful Diversity in Steady-State Genetic Algorithms, Lozano, M., Herrera F., and Cano J. R. , Information Sciences, (2012)
2011
A double axis classi, Gacto, M. J., Alcalá R., and Herrera F. , 9th International Workshop on Fuzzy Logic and Applications (WILF), (2011)
A Fast and Scalable Multi-Objective Genetic Fuzzy System for Linguistic Fuzzy Modeling in High-Dimensional Regression Problems, Alcalá, R., Gacto M. J., and Herrera F. , IEEE Transactions on Fuzzy Systems, Volume 19, Number 4, p.666-681, (2011)
A Genetic Tuning to Improve the Performance of Fuzzy Rule-Based Classification Systems with Interval-Valued Fuzzy Sets: Degree of Ignorance and Lateral Position, Sanz, J., Fernández A., Bustince H., and Herrera F. , International Journal of Approximate Reasoning, Volume 52, Number 6, p.751-766, (2011)
Addressing Data Complexity for Imbalanced Data Sets: Analysis of SMOTE-based Oversampling and Evolutionary Undersampling, Luengo, J., Fernández A., García S., and Herrera F. , Soft Computing, Volume 15, Number 10, p.1909-1936, (2011)
An overview on Subgroup Discovery: Foundations and Applications, Herrera, F., Carmona C. J., González P., and del Jesus M. J. , Knowledge and Information Systems, Volume 29, Number 3, p.495-525, (2011) PDF icon 2011-Herrera-KAIS.pdf (553.73 KB)
Analysis of the Impact of Using Different Diversity Functions for the Subgroup Discovery Algorithm NMEEF-SD, Carmona, C. J., González P., del Jesus M. J., and Herrera F. , 5th International Workshop on Genetic and Evolutionary Fuzzy Systems (GEFS), April, Paris (France), p.17-23, (2011) PDF icon 2011 - GEFS.pdf (6.67 MB)
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, Gacto, M. J., Alcalá R., and Herrera F. , 5th International Workshop On Genetic And Evolutionary Fuzzy Systems (GEFS), April, (2011)
Evolutionary Selection of Hyperrectangles in Nested Generalized Exemplar Learning, García, S., Derrac J., Luengo J., Carmona C. J., and Herrera F. , Applied Soft Computing, Volume 11, Number 3, p.3032-3045, (2011) PDF icon 2011-Garcia-ASOC.pdf (2.07 MB)
Interpretability of Linguistic Fuzzy Rule-Based Systems: An Overview of Interpretability Measures, Gacto, M. J., Alcalá R., and Herrera F. , Information Sciences, Volume 181, Number 20, p.4340–4360, (2011)
KEEL Data-Mining Software Tool: Data Set Repository, Integration of Algorithms and Experimental Analysis Framework, Alcalá-Fdez, J., Fernández A., Luengo J., Derrac J., García S., Sánchez L., and Herrera F. , Journal of Multiple-Valued Logic and Soft Computing, Volume 17, Number 2-3, p.255-287, (2011)
2010
A Preliminary Study on the Selection of Generalized Instances for Imbalanced Classification, García, S., Derrac J., Triguero I., Carmona C. J., and Herrera F. , Twenty Third International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems (IEA/AIE), Cordoba, p.601-610, (2010) PDF icon 2010 - IEA-AEI.pdf (211.57 KB)
A Review on Evolutionary Prototype Selection, García, S., Cano J. R., and Herrera F. , Intelligent Systems for Automated Learning and Adaptation: Emerging Trends and Applications, p.92–113, (2010)
Advanced nonparametric tests for multiple comparisons in the design of experiments in computational intelligence and data mining: Experimental Analysis of Power, García, S., Fernández A., Luengo J., and Herrera F. , Information Sciences, Volume 180, p.2044–2064, (2010)
Analysing the Hierarchical Fuzzy Rule Based Classification Systems with Genetic Rule Selection, Fernández, A., del Jesus M. J., and Herrera F. , 4th International Workshop on Genetic and Evolutionary Fuzzy Systems (GEFS), March, Mieres (Spain), p.69-74, (2010)
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, Gacto, M. J., Alcalá R., and Herrera F. , LNAI 6097, June, Córdoba, p.228-238, (2010)
Genetics-Based Machine Learning for Rule Induction: State of the Art, Taxonomy and Comparative Study, Fernández, A., Luengo J., García S., Bernadó-Mansilla E., and Herrera F. , IEEE Transactions on Evolutionary Computation, Volume 14, Number 6, p.913-941, (2010)
Improving the Performance of Fuzzy Rule-Based Classification Systems with Interval-Valued Fuzzy Sets and Genetic Amplitude Tuning, Sanz, J., Fernández A., Bustince H., and Herrera F. , Information Sciences, Volume 180, Number 19, p.3674-3685, (2010)
Indice de Interpretabilidad Semántica para el Ajuste de Sistemas Basados en Reglas Difusas y Selección de Reglas Mediante un Algoritmo Evolutivo Multi-Objetivo, Gacto, M. J., Alcalá R., and Herrera F. , XV Edición del Congreso Español sobre Tecnologías y Lógica Fuzzy (ESTYLF), February, Huelva, p.73-78, (2010)
Integration of an Index to Preserve the Semantic Interpretability in the Multi-Objective Evolutionary Rule Selection and Tuning of Linguistic Fuzzy Systems, Gacto, M. J., Alcalá R., and Herrera F. , IEEE Transactions on Fuzzy Systems, Volume 18, Number 3, p.515-531, (2010)
Multi-class Imbalanced Data-Sets with Linguistic Fuzzy Rule Based Classification Systems Based on Pairwise Learning, Fernández, A., del Jesus M. J., and Herrera F. , 13th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU), June, Volume 6178, Dortmund (Germany), p.89-98, (2010)
NMEEF-SD: Non-dominated Multi-objective Evolutionary algorithm for Extracting Fuzzy rules in Subgroup Discovery, Carmona, C. J., González P., del Jesus M. J., and Herrera F. , IEEE Transactions on Fuzzy Systems, Volume 18, Number 5, p.958-970, (2010) PDF icon 2010-Carmona-TFS.pdf (457.11 KB)
On the 2-Tuples Based Genetic Tuning Performance for Fuzzy Rule Based Classification Systems in Imbalanced Data-Sets, Fernández, A., del Jesus M. J., and Herrera F. , Information Sciences, Volume 180, Number 8, p.1268-1291, (2010)
Solving Multi-Class Problems with Linguistic Fuzzy Rule Based Classification Systems Based on Pairwise Learning and Preference Relations, Fernández, A., Calderón M., Barrenechea E., Bustince H., and Herrera F. , Fuzzy Sets and Systems, Volume 161, Number 23, p.3064-3080, (2010)
2009
A Multiobjective Evolutionary Algorithm for Tuning Fuzzy Rule Based Systems with Measures for Preserving Interpretability, Gacto, M. J., Alcalá R., and Herrera F. , Proceedings of the Joint International Fuzzy Systems Association World Congress and the European Society for Fuzzy Logic and Technology Conference (IFSA), July, Lisbon, Portugal, p.1146-1151, (2009)
Adaptation and Application of Multi-Objective Evolutionary Algorithms for Rule Reduction and Parameter Tuning of Fuzzy Rule-Based Systems, Gacto, M. J., Alcalá R., and Herrera F. , Soft Computing, Volume 13, Number 5, p.419-436, (2009)
Addressing Data-Complexity for Imbalanced Data-sets: A Preliminary Study on the Use of Preprocessing for C4.5, Luengo, J., Fernández A., Herrera F., and García S. , 9th International Conference on Intelligent Systems Designs and Applications (ISDA), p.523-528, (2009)
Algoritmo Genético Multi-Objetivo Avanzado para el ajuste de un sistema difuso aplicado al Control de Sistemas de Ventilación, Calefacción y Aire Acondicionado, Gacto, M. J., Alcalá R., and Herrera F. , Proceedings of the Congreso Español sobre Metaheurísticas, Algoritmos Evolutivos y Bioinspirados (MAEB), February, p.595-602, (2009)
An analysis of evolutionary algorithms with different types of fuzzy rules in subgroup discovery, Carmona, C. J., González P., del Jesus M. J., and Herrera F. , IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), August, ICC Jeju, Jeju Island, Korea, p.1706-1711, (2009) PDF icon 2009 - FUZZIEEE.pdf (192.81 KB)
Diagnose of Effective Evolutionary Prototype Selection using an Overlapping Measure, García, S., Cano J. R., Bernadó-Mansilla E., and Herrera F. , International Journal of Pattern Recognition and Artificial Intelligence, Volume 23, Number 8, p.1527-1548, (2009)
Enhancing the Effectiveness and Interpretability of Decision Tree and Rule Induction Classifiers with Evolutionary Training Set Selection over Imbalanced Problems, García, S., Fernández A., and Herrera F. , Applied Soft Computing, Volume 9, p.1304-1314, (2009)
Evolutionary algorithms for subgroup discovery in e-learning: A practical application using Moodle data, Romero, C., González P., Ventura S., del Jesus M. J., and Herrera F. , Expert Systems with Applications, Volume 36, p.1632-1644, (2009)
Genetic Cooperative-Competitive Fuzzy Rule Based Learning Method using Genetic Programming for Highly Imbalanced Data-Sets, Fernández, A., Berlanga F. J., del Jesus M. J., and Herrera F. , 13 th International Fuzzy Systems Association World Congress and 6th European Society for Fuzzy Logic and Tecnology Conference (IFSA-EUSFLAT), Lisbon (Portugal), p.42-47, (2009)
Handling High-Dimensional Regression Problems by Means of an Efficient Multi-Objective Evolutionary Algorithm, Gacto, M. J., Alcalá R., and Herrera F. , 9th International Conference on Intelligent Systems Design and Applications (ISDA), November, Pisa (Italy), p.109-114, (2009)
Hierarchical fuzzy rule based classfication systems with genetic rule selection for imbalanced data-sets, Fernández, A., del Jesus M. J., and Herrera F. , International Journal of Approximate Reasoning, Volume 50, p.561-577, (2009)
Improving Fuzzy Logic Controllers Obtained by Experts: A Case Study in HVAC Systems, Alcalá, R., Alcalá-Fdez J., Gacto M. J., and Herrera F. , Applied Intelligence, Volume 31, Number 1, p.15-30, (2009)
Improving the Performance of Fuzzy Rule Based Classification Systems for Highly Imbalanced Data-sets Using an Evolutionary Adaptive Inference System, Fernández, A., del Jesus M. J., and Herrera F. , 10th International Work-Conference on Artificial Neural Networks (IWANN), June, Volume 5517, Salamanca (Spain), p.294-301,, (2009)
KEEL: A Software Tool to Assess Evolutionary Algorithms for Data Mining Problems, Alcalá-Fdez, J., Sánchez L., García S., del Jesus M. J., Ventura S., Garrell J.M., Otero J., Romero C., Bacardit J., Rivas V. M., et al. , Soft Computing, Volume 13, Number 3, p.307-318, (2009)
Learning the Membership Function Contexts for Mining Fuzzy Association Rules by Using Genetic Algorithms, Alcalá-Fdez, J., Alcalá R., Gacto M. J., and Herrera F. , Fuzzy Sets and Systems, Volume 160, Number 7, p.905-921, (2009)
Non-dominated Multi-objective Evolutionary Algorithm Based on Fuzzy Rules Extraction for Subgroup Discovery, Carmona, C. J., González P., del Jesus M. J., and Herrera F. , Proceedings of the Fourth International Conference on Hybrid Artificial Intelligence Systems (HAIS), June, Volume 5572, Salamanca (Spain), p.573-580, (2009) PDF icon 2009 - HAIS.pdf (166.16 KB)
On the influence of an adaptive inference system in fuzzy rule-based classification sytems for imbalanced data-sets, Fernández, A., Herrera F., and del Jesus M. J. , Expert Systems with Applications, Volume 36, Number 6, p.9805-9812, (2009)
Un Primer Estudio sobre la Utilización de Selección Evolutiva de Conjuntos de Entrenamiento en Problemas de Clasificación con Clases no Balanceadas y Árboles de Decisión, García, S., Fernández A., and Herrera F. , Proceedings of VI Congreso Español sobre Metaheurísticas, Algoritmos Evolutivos y Bioinspirados (MAEB), February, Málaga (Spain), p.183-190, (2009)
2008
A memetic algorithm for Evolutionary Prototype Selection: A Scaling Up Approach, García, S., Cano J. R., and Herrera F. , Pattern Recognition, Volume 41, Number 8, p.2693-2709, (2008)
A Novel Genetic Cooperative-Competitive Fuzzy Rule Based Learning Method using Genetic Programming for High Dimensional Problems, Berlanga, F. J., del Jesus M. J., and Herrera F. , 3rd International Workshop on Genetic and Evolving Fuzzy Systems (GEFS), WittenBommerholz (Germany), p.101-106, (2008)
A Study of the Behaviour of Linguistic Fuzzy Rule Based Classification Systems in the Framework of Imbalanced Data Sets, Fernández, A., García S., del Jesus M. J., and Herrera F. , Fuzzy Sets and Systems, Volume 159, Number 18, p.2378-2398, (2008)
An Improved Multi-Objective Genetic Algorithm for Tuning Linguistic Fuzzy System, Gacto, M. J., Alcalá R., and Herrera F. , Proceedings of the 2008 International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU), June, p.1121-1128, (2008)
Estudio de la influencia de las medidas de complejidad de los datos en los Sistemas de Clasifcación Basados en Reglas Difusas: Análisis de la Razón Discriminante de Fisher, Luengo, J., García S., Cano J. R., and Herrera F. , XIV Congreso Español sobre Tecnologías y Lógica Fuzzy (ESTYLF), September, Mieres (Spain), p.257-263, (2008)
Influencia de la granularidad y de las medidas de calidad en SDIGA, González, P., Carmona C. J., del Jesus M. J., and Herrera F. , XIV Congreso Español de Tecnologías y Lógica Difusa( ESTYLF), September, Langreo-Mieres (Spain), (2008) PDF icon 2008b - ESTYLF.pdf (338.36 KB)
KEEL: A Data Mining Software Tool Integrating Genetic Fuzzy Systems, Alcalá-Fdez, J., García S., Berlanga F. J., Fernández A., Sánchez L., del Jesus M. J., and Herrera F. , 3rd International Workshop on Genetic and Evolving Fuzzy Systems (GEFS), WittenBommerholz (Germany), p.83-88, (2008)
Making CN2-SD Subgroup Discovery Algorithm scalable to Large Size Data Sets using Instance Selection, Cano, J. R., Herrera F., Lozano M., and García S. , Expert Systems with Applications, Volume 35, p.1949-1965, (2008)
Multi-Objective Genetic Fuzzy Systems: On the Necessity of Including Expert Knowledge in the MOEA Design Process, Gacto, M. J., Alcalá R., and Herrera F. , Proceedings of the 2008 International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU), June, p.1446-1453, (2008)
On the use of Multiobjective Genetic Algorithms to Improve the Accuracy-Interpretability Trade-Off of Fuzzy Rule-Based Systems, Alcalá, R., Alcalá-Fdez J., Gacto M. J., and Herrera F. , Multi-objective Evolutionary Algorithms for Knowledge Discovery from Data Bases, Volume 98, (2008)
Replacement strategies to preserve useful diversity in steady-state genetic algorithms, Lozano, Manuel, Cano J. R., and Herrera F. , Information Sciences, Volume 178, Number 23, p.4421–4433, (2008)
Subgroup Discovery in Large Size Data Sets Preprocessed Using Stratified Instance Selection for Increasing the Presence of Minority Classes, Cano, J. R., García S., and Herrera F. , Pattern Recognition Letters, Volume 29, p.2156-2164, (2008)
2007
A Multi-objectiveGenetic Algorithm for Tuning and Rule Selection to Obtain Accurate and Compact Linguistic Fuzzy Rule-Based Systems, Alcalá, R., Gacto M. J., Herrera F., and Alcalá-Fdez J. , International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, Volume 15, Number 5, p.539–557, (2007)
A study on the Use of the Fuzzy Reasoning Method based on the Winning Rule Vs. Voting Procedure for Classification with Imbalanced Data Sets, Fernández, A., García S., del Jesus M. J., and Herrera F. , Proceedings of the 9th International Work-Conference on Artificial Neural Networks (IWANN), June, San Sebastián (Spain), p.375-382, (2007)
An Analysis of the Rule Weights and Fuzzy Reasoning Methods for Linguistic Rule Based Classification Systems Applied to Problems with Highly Imbalanced Data Sets, Fernández, A., García S., del Jesus M. J., and Herrera F. , International Workshop on Fuzzy Logic and Applications (WILF), July, Genova (Italy), p.170-179, (2007)
Análisis of Evolutionary Prototype Selection by means of a Data Complexity Measure based on Class Separabilty, Cano, J. R., García S., Herrera F., and Bernadó-Mansilla E. , Actas del Taller de Minería de Datos y Aprendizaje (TAMIDA), Zaragoza, p.145-152, (2007)
Aplicación de Algoritmos Evolutivos de Descubrimiento de Subgrupos en e-Learning: un Caso de Estudio, Romero, C., González P., Ventura S., del Jesus M. J., and Herrera F. , V Congreso Español sobre Metaheurísticas, Algoritmos Evolutivos y Bioinspirados (MAEB), Tenerife (Spain), p.493-500, (2007)
Aprendizaje Evolutivo de los Contextos de las Funciones de Pertenencia para Extraer Reglas de Asociación Difusas, Alcalá-Fdez, J., Alcalá R., Gacto M. J., and Herrera F. , Proceedings of the II Congreso Español de Informática (CEDI 2007). II Simposio sobre Lógica Fuzzy y Soft Computing (LFSC), September, p.25-32, (2007)
Evolutionary fuzzy rule induction process for subgroup discovery: a case study in marketing, del Jesus, M. J., González P., Herrera F., and Mesonero M. , IEEE Transactions on Fuzzy Systems, Volume 15, Number 4, p.578-592, (2007)
Evolutionary Stratified Training Set Selection for Extracting Classification Rules with trade off Precision-Interpretability, Cano, J. R., Herrera F., and Lozano M. , Data & Knowledge Engineering, Volume 60, Number 1, p.90-108, (2007)
Genetic Learning of Membership Functions for Mining Fuzzy Association Rules, Alcalá, R., Alcalá-Fdez J., Gacto M. J., and Herrera F. , Proceedings of the 16th IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), July, London (United Kingdom), p.1538-1543, (2007)
Multiobjective genetic algorithm for extractiong subgroup discovery fuzzy rules, González, P., del Jesus M. J., and Herrera F. , 2007 IEEE Symposium on Computational Intelligence in Multicriteria Decision Making (IEEE MCDM), Honolulu (USA), p.50-57, (2007)
Rule Base Reduction and Genetic Tuning of Fuzzy Systems based on the Linguistic 3-Tuples Representation, Alcalá, R., Alcalá-Fdez J., Gacto M. J., and Herrera F. , Soft Computing, Volume 11, Number 5, p.401-419, (2007)
Statistical Comparisons by Means of Non-Parametric Tests: A Case Study on Genetic Based Machine Learning, García, S., Fernández A., Benítez A.D., and Herrera F. , Proceedings of the II Congreso Español de Informática (CEDI 2007). V Taller Nacional de Minería de Datos y Aprendizaje (TAMIDA), September, Zaragoza (Spain), p.95-104, (2007)
Un algoritmo memético para la selección de prototipos: Una propuesta eficiente para problemas de tamaño medio, García, S., Cano J. R., and Herrera F. , Proceedings Congreso Español sobre Metaheurísticas, Algoritmos Evolutivos y Bioinspirados (MAEB), Tenerife, (2007)
2006
A first study on the use of fuzzy rule based classification systems for problems with imbalanced data sets, del Jesus, M. J., Fernández A., García S., and Herrera F. , Proceedings of the Symposium on Fuzzy Systems in Computer Science (FSCS), September, Magdeburg (Germany), p.63-72, (2006)
A Genetic-Programming-Based Approach for the Learning of Compact Fuzzy Rule-Based Classification Systems, Berlanga, F. J., del Jesus M. J., Gacto M. J., and Herrera F. , The Eighth International Conference on Artificial Intelligence and Soft Computing (ICAISC), Volume 4029, Zakopane (Poland), p.182-191, (2006)
A proposal of Evolutionary Prototype Selection for Class Imbalance Problems, García, S., Cano J. R., Fernández A., and Herrera F. , Proceedings of the 7th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL), Volume 4224, p.1415-1423, (2006)
Fuzzy Rule Reduction and Tuning of Fuzzy Logic Controllers for a HVAC System, Alcalá, R., Alcalá-Fdez J., Gacto M. J., and Herrera F. , Fuzzy Applications in Industrial Engineering, Studies in Fuzziness and Soft Computing, Volume 201, p.89-117, (2006)
Genetic Lateral and Amplitude Tuning with Rule Selection for Fuzzy Control of Heating, Ventilating and Air Conditioning Systems, Alcalá, R., Alcalá-Fdez J., Berlanga F. J., Gacto M. J., and Herrera F. , 19th International Conference on Industrial & Engineering Applications of Artificial Intelligence & Expert Systems (IEA/AIE), Volume 4031, Annecy (France), p.452-461, (2006)
Improving Fuzzy Rule-Based Decision Models by Means of a Genetic 2-Tuples Based Tuning and the Rule Selection, Alcalá, R., Alcalá-Fdez J., Berlanga F. J., Gacto M. J., and Herrera F. , Modeling Decisions for Artificial Intelligence (MDAI), Volume 3885, Tarragona (Spain), p.317-328, (2006)
Incorporating Knowledge in Evolutionary Prototype Selection, García, S., Cano J. R., and Herrera F. , Proceedings of the 7th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL), Volume 4224, p.1358-1366, (2006)
Multiobjective Evolutionary Induction of Subgroup Discovery Fuzzy Rules: A Case Study in Marketing, Berlanga, F. J., del Jesus M. J., González P., Herrera F., and Mesonero M. , 6th Industrial Conference on Data Mining (ICDM), Volume 4065, Leipzig (Germany), p.337-349, (2006)
Obtaining Compact and Still Accurate Linguistic Fuzzy Rule-Based Systems by Using Multi-Objetive Genetic Algorithms, Alcalá, R., Alcalá-Fdez J., Gacto M. J., and Herrera F. , Proceedings of the Symposium on Fuzzy Systems in Computer Science (FSCS), p.53-62, (2006)
On the Combination of Evolutionary Algorithms and Stratified Strategies for Training Set Selection in Data Mining, Cano, J. R., Herrera F., and Lozano M. , Applied Soft Computing, Volume 6, p.323-332, (2006)
Un primer estudio sobre el uso de los sistemas de clasificación basados en reglas difusas en problemas de clasificación con clases no balanceadas, Fernández, A., García S., Herrera F., and del Jesus M. J. , Proceedings of the XIII Congreso Español sobre Tecnologías y Lógica Fuzzy (ESTYLF), September, Ciudad Real (Spain), p.89-95, (2006)
2005
A Study on the Combination of Evolutionary Algorithms and Stratified Strategies for Training Set Selection in Data Mining, Cano, J. R., Herrera F., and Lozano M. , Soft Computing: Methodologies and Applications, p.271-284, (2005)
Ajuste Evolutivo Lateral y de Amplitud de etiquetas para Sistemas Basados en Reglas Difusas, Alcalá, R., Alcalá-Fdez J., Gacto M. J., and Herrera F. , Simposio de Inteligencia Computacional (SICO), Granada (Spain), p.481-488, (2005)
Aprendizaje de reglas difusas mediante programación genética en problemas con alta dimensionalidad, Berlanga, F. J., del Jesus M. J., and Herrera F. , I Simposio sobre Lógica Fuzzy y Soft Computing (LFSC), Granada (Spain), p.93-100, (2005)
Evolutionary induction of descriptive fuzzy rules in a market problem, del Jesus, M. J., González P., Herrera F., and Mesonero M. , I International Workshop on Genetic Fuzzy Systems (GFS), Granada (Spain), p.57-63, (2005)
Evolutionary Induction of Descriptive Rules in a Market Problem, del Jesus, M. J., González P., Herrera F., and Mesonero M. , Intelligent Data Mining. Techniques and Applications, Studies in Computational Intelligence, Volume 5, p.267-292, (2005)
Genetic Lateral and Amplitude Tuning of Membership Functions for Fuzzy Systems, Alcalá, R., Alcalá-Fdez J., Gacto M. J., and Herrera F. , Proceedings of the 2nd International Conference on Machine Intelligence (ACIDCA-ICMI), p.589-595, (2005)
Genetic tuning of fuzzy rule deep structures preserving interpretability for linguistic modeling, Casillas, J., Cordón O., del Jesus M. J., and Herrera F. , IEEE Transactions on Fuzzy Systems, Volume 13, Number 1, p.13-29, (2005)
Inducción evolutiva multiobjetivo de reglas de descripción de subgrupos en un problema de marketing, del Jesus, M. J., González P., and Herrera F. , IV Congreso Español sobre Metaheurísticas, Algoritmos Evolutivos y Bioinspirados (MAEB), Granada (Spain), p.661-669, (2005)
Instance Selection Using Evolutionary Algorithms: An Experimental Study, Cano, J. R., Herrera F., and Lozano M. , Knowledge Discovery in Advanced Information Systems, p.127-152, (2005)
Learning compact fuzzy rule-based classification systems with genetic programming, Berlanga, F. J., del Jesus M. J., and Herrera F. , 4th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT), Barcelona (Spain), p.1027-1032, (2005)
Learning fuzzy rules using genetic programming: Context-free grammar definition for high-dimensionality problems, Berlanga, F. J., del Jesus M. J., and Herrera F. , I International Workshop on Genetic Fuzzy Systems (GFS), Granada (Spain), p.136-141, (2005)
Multiobjective evolutionary induction of subgroup discovery rules in a market problem, Berlanga, F. J., del Jesus M. J., González P., and Herrera F. , 2nd International Conference on Machine Intelligence (ACIDCA-ICMI), Tozeur (Tunisia), p.610-617, (2005)
Strategies for Scaling Up Evolutionary Instance Reduction Algorithms for Data Mining, Cano, J. R., Herrera F., and Lozano M. , Evolutionary Computation in Data Mining, p.21-39, (2005)
Stratification for Scaling Up Evolutionary Prototype Selection, Cano, J. R., Herrera F., and Lozano M. , Pattern Recognition Letters, Volume 26, p.953-963, (2005)
2004
Algoritmo Evolutivo de Extracción de reglas de Asociación aplicado a un problema de marketing, del Jesus, M. J., González P., Herrera F., and Mesonero M. , III Congreso Español de Metaheurísticas, Algoritmos Evolutivos y Bioinspirados(MAEB), Córdoba (Spain), p.102-104, (2004)
Extracción de reglas DNF difusas en un problema de marketing, del Jesus, M. J., González P., Herrera F., and Mesonero M. , XII Congreso Español de Tecnologías y Lógica Difusa(ESTYLF), Jaén (Spain), p.351-356, (2004)
Selección Evolutiva Estratificada de Conjuntos de Entrenamiento para la Obtención de Bases de Reglas con un Alto Equilibrio entre Precisión e Interpretabilidad, Cano, J. R., Herrera F., and Lozano M. , Tendencias de la Minería de Datos en Spain., p.263 - 274, (2004)
2003
An Study on the Combination of Evolutionary Algorithms and Stratified Strategies for Training Set Selection in Data Mining, Cano, J. R., Herrera F., and Lozano M. , Proceedings of the 8th Online World Conference on Soft Computing in Industrial Applications, September, (2003)
Extracción Evolutiva de Reglas de Asociación en un Servicio de Urgencias Psiquiátricas, Aguilera, J.J., del Jesus M. J., González P., Herrera F., Navío M., and Sáinz J. , II Congreso español sobre Metaheurísticas, Algoritmos evolutivos y bioinspirados(MAEB), Gijón(Spain), p.548-555, (2003)
Linguistic Modeling with Hierarchical Systems of Weighted Linguistic Rules, Alcalá, R., Cano J. R., Cordón O., Herrera F., Villar P., and Zwir I. , International Journal of Approximate Reasoning, Volume 32, Number 2-3, p.187-215, (2003)
Replacement Strategies to Maintain Useful Diversity in Steady-State Genetic Algorithms, Lozano, M., Herrera F., and Cano J. R. , Proceedings of the 8th Online World Conference on Soft Computing in Industrial Applications, September, (2003)
Using Evolutionary Algorithms as Instance Selection for Data Reduction in KDD: an Experimental Study, Cano, J. R., Herrera F., and Lozano M. , IEEE Transactions on Evolutionary Computation, Volume 7, Number 6, p.561-575, (2003)
2002
A GRASP Algorithm for Clustering, Cano, J. R., Cordón O., Herrera F., and Sánchez Luciano , Proceedings of the 8th Ibero-American Conference on Artifical Intelligence, Seville, Spain, November 12-15, 2002,, p.214–223, (2002)
A greedy randomized adaptive search procedure applied to the clustering problem as an initialization process using K-Means as a local search procedure, Cano, J. R., Cordón O., Herrera F., and Sánchez Luciano , Journal of Intelligent and Fuzzy Systems, Volume 12, Number 3-4, p.235–242, (2002)
Some Relationships between fuzzy and random set-based classifiers and models, Sánchez, L., Casillas J., Cordón O., del Jesus M. J., and Herrera F. , International Journal of Approximate Reasoning, Volume 29, p.175-213, (2002)