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INICIO | 19 de mayo de 2024
  

Rule-based fuzzy object similarity.

Título inglés Rule-based fuzzy object similarity.
Título español Semejanza difusa de objetos basada en reglas.
Autor/es Bunke, Horst ; Fábregas, Xavier ; Kandel, Abraham
Organización Dep. Comput. Sci. Univ. Bern, Berna, Suiza;Dep. Comput. Sci. Eng. Univ. South Florida, Tampa (Florida), Estados Unidos
Revista 1134-5632
Publicación 2001, 8 (2): 113-128, 19 Ref.
Tipo de documento articulo
Idioma Inglés
Resumen inglés A new similarity measure for objects that are represented by feature vectors of fixed dimension is introduced. It can simultaneously deal with numeric and symbolic features. Also, it can tolerate missing feature values. The similarity measure between two objects is described in terms of the similarity of their features. IF-THEN rules are being used to model the individual contribution of each feature to the global similarity measure between a pair of objects. The proposed similarity measure is based on fuzzy sets and this allows us to deal with vague, uncertain and distorted information in a natural way. Several formal properties of the proposed similarity measure are derived; in particular, we show that the measure can be used to model the Euclidean distance as well as other, non-Euclidean distance functions. Also, an application of the proposed similarity measure to nearest-neighbor classification in a medical expert system is described.
Clasificación UNESCO 110208
Palabras clave español Inteligencia artificial ; Teoría de la semejanza ; Variables difusas
Código MathReviews MR1864068
Código Z-Math Zbl 1014.68162
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Equipo DML-E
Instituto de Ciencias Matemáticas (ICMAT - CSIC)
rmm()icmat.es