A first study on the use of interval-valued fuzzy sets with genetic tuning for classification with imbalanced data sets
Fecha
2009Versión
Acceso abierto / Sarbide irekia
Tipo
Contribución a congreso / Biltzarrerako ekarpena
Versión
Versión aceptada / Onetsi den bertsioa
Impacto
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10.1007/978-3-642-02319-4_70
Resumen
Classification with imbalanced data-sets is one of the recent
challenging problems in Data Mining. In this framework, the class dis-
tribution is not uniform and the separability between the classes is often
difficult. From the available techniques in the Machine Learning field,
we focus on the use of Fuzzy Rule Based Classification Systems, as they
provide an interpretable model for the end ...
[++]
Classification with imbalanced data-sets is one of the recent
challenging problems in Data Mining. In this framework, the class dis-
tribution is not uniform and the separability between the classes is often
difficult. From the available techniques in the Machine Learning field,
we focus on the use of Fuzzy Rule Based Classification Systems, as they
provide an interpretable model for the end user by means of linguistic
variables.
The aim of this work is to increase the performance of fuzzy modeling
by adding a higher degree of knowledge by means of the use of Interval-
valued Fuzzy Sets. Furthermore, we will contextualize the Interval-valued
Fuzzy Sets with a post-processing genetic tuning of the amplitude of
their upper bounds in order to enhance the global behaviour of this
methodology. [--]
Materias
Fuzzy rule-based classification systems,
Interval-valued fuzzy sets,
Tuning,
Genetic algorithms,
Imbalanced data-sets
Editor
Springer
Publicado en
Corchado, E.; Wu, X.; Oja, E.; Herrero, Á.; Baruque, B. (Eds.). Hybrid Artificial Intelligence Systems: 4th International Conference, HAIS 2009: proceedings. Berlín: Springer; 2009. p.581-588 978-3-642-02318-7
Departamento
Universidad Pública de Navarra. Departamento de Automática y Computación /
Nafarroako Unibertsitate Publikoa. Automatika eta Konputazioa Saila
Versión del editor
Entidades Financiadoras
This work has been supported by the Spanish Ministry of Science and Technology
under projects TIN2008-06681-C06-01 and TIN2007-65981.