Fuzzy Classification of Symbolic Objects

• Autorzy: Małgorzata Machowska-Szewczyk
• Języki publikacji: EN

Abstrakty

EN

The aim of this work is to present fuzzy clustering algorithm for objects, which can be described by mixed feature-type symbolic data and fuzzy data. The main idea is the transformation of mixed feature-type symbolic data and fuzzy data into histogram-valued symbolic data. Fuzzy classification is very useful in case, when classes are difficult separated, mixed objects can be classified into class with the fixed degree of membership. (original abstract)

Słowa kluczowe

EN

Classification; Fuzzy sets

PL

Klasyfikacja; Zbiory rozmyte

• Czasopismo: Metody Ilościowe w Badaniach Ekonomicznych / Szkoła Główna Gospodarstwa Wiejskiego
• Rocznik: 2013
• Tom: 14(XIV)
• Numer: nr 2
• Strony: 51--60

Twórcy

autor

Małgorzata Machowska-Szewczyk

• Zachodniopomorski Uniwersytet Technologiczny w Szczecinie

Bibliografia

• Bock H. H., Diday E. (2000) Analysis of Symbolic Data. Exploratory Methods for Extracting Statistical Information from Complex Data, Springer-Verlag, Berlin, Heidelberg.
• De Carvalho F.A.T. (1995) Histograms in symbolic data analysis. Annals of Operations Research 55, 229-322.
• De Carvalho F.A.T., de Souza R. (2010) Unsupervised pattern recognition models for mixed feature-type symbolic data, Pattern Recognition Letters 31, 430-443.
• Diday E., Simon J.C. (1976) Clustering analysis. In: Fu, K.S. (Ed.), Digital Pattern Clasification. Springer, Berlin, 47-94.
• Zimmermann H.J. (1991) Fuzzy Set Theory and Its Applications, Kluwer, Dordrecht.