His main research concerns Artificial intelligence, Machine learning, Fuzzy logic, Data mining and Fuzzy set. His Artificial intelligence study typically links adjacent topics like Linguistics. The concepts of his Machine learning study are interwoven with issues in Set and Genetic fuzzy systems.
As a part of the same scientific study, he usually deals with the Set, concentrating on Nonparametric statistics and frequently concerns with Statistical hypothesis testing. His Fuzzy logic study integrates concerns from other disciplines, such as Multiplicative function, Group decision-making and Preference, Preference theory. In Data mining, he works on issues like Data set, which are connected to Algorithm.
His primary areas of study are Artificial intelligence, Machine learning, Data mining, Fuzzy logic and Fuzzy rule. His research links Pattern recognition with Artificial intelligence. Francisco Herrera has researched Machine learning in several fields, including Classifier and Set.
The various areas that Francisco Herrera examines in his Data mining study include Class, Preprocessor, Feature selection and k-nearest neighbors algorithm. His work deals with themes such as Mathematical optimization, Preference and Group decision-making, which intersect with Fuzzy logic. His work on Rule-based machine translation as part of his general Linguistics study is frequently connected to Term, thereby bridging the divide between different branches of science.
His primary scientific interests are in Artificial intelligence, Machine learning, Big data, Data mining and Group decision-making. He has included themes like Natural language processing, Set and Pattern recognition in his Artificial intelligence study. Many of his studies on Machine learning involve topics that are commonly interrelated, such as Optimization problem.
As part of one scientific family, Francisco Herrera deals mainly with the area of Big data, narrowing it down to issues related to the Data science, and often Taxonomy. His Group decision-making research is multidisciplinary, incorporating perspectives in Consistency, Social network, Cluster analysis, Fuzzy logic and Preference. His work in Preference addresses subjects such as Set, which are connected to disciplines such as Linguistics.
Francisco Herrera mainly investigates Artificial intelligence, Group decision-making, Machine learning, Term and Preference. His Artificial intelligence study frequently draws connections to adjacent fields such as Pattern recognition. His research integrates issues of Consistency, Social network, Cluster analysis, Fuzzy logic and Operations research in his study of Group decision-making.
His Fuzzy logic research includes elements of Multiplicative function and Consistency. He is interested in Ensemble selection, which is a branch of Machine learning. His work investigates the relationship between Convolutional neural network and topics such as Robustness that intersect with problems in Data mining.
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A 2-tuple fuzzy linguistic representation model for computing with words
F. Herrera;L. Martinez.
IEEE Transactions on Fuzzy Systems (2000)
A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithms
Joaquín Derrac;Salvador García;Daniel Molina;Francisco Herrera.
Swarm and evolutionary computation (2011)
KEEL Data-Mining Software Tool: Data Set Repository, Integration of Algorithms and Experimental Analysis Framework
J. Alcalá-Fdez;A. Fernández;J. Luengo;J. Derrac.
soft computing (2011)
Linguistic decision analysis: steps for solving decision problems under linguistic information
F. Herrera;E. Herrera-Viedma.
Fuzzy Sets and Systems (2000)
A Review on Ensembles for the Class Imbalance Problem: Bagging-, Boosting-, and Hybrid-Based Approaches
M. Galar;A. Fernandez;E. Barrenechea;H. Bustince.
systems man and cybernetics (2012)
Tackling Real-Coded Genetic Algorithms: Operators and Tools for Behavioural Analysis
F. Herrera;M. Lozano;J. L. Verdegay.
Artificial Intelligence Review (1998)
Hesitant Fuzzy Linguistic Term Sets for Decision Making
R. M. Rodriguez;L. Martinez;F. Herrera.
IEEE Transactions on Fuzzy Systems (2012)
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
Salvador García;Daniel Molina;Manuel Lozano;Francisco Herrera.
Journal of Heuristics (2009)
Advanced nonparametric tests for multiple comparisons in the design of experiments in computational intelligence and data mining: Experimental analysis of power
Salvador García;Alberto Fernández;Julián Luengo;Francisco Herrera.
Information Sciences (2010)
Genetic Fuzzy Systems: Evolutionary Tuning And Learning Of Fuzzy Knowledge Bases
Oscar Cordón;Francisco Herrera;Frank Hoffmann;Luis Magdalena.
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