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Modelling of Rough-Fuzzy Classifier

Authors: Jirava Pavel | Křupka Jiří

Year: 2008

Type of publication: článek v odborném periodiku

Name of source: WSEAS Transactions on Systems

Publisher name: WSEAS Press

Place: Atény

Page from-to: 251-262

Titles:

Language	Name	Abstract	Keywords
cze	Modelování rough fuzzy klasifikátoru	V článku je představen hybridní model klasifikátoru založený na fuzzy a rough množinách. Navržené algoritmy jsou realizovány v Matlabu a model je poté testován na různých datových množinách. Na závěr jsou jeho výstupy porovnány s jinými metodami	klasifikase; rough sets; fuzzy sets; hybridní model
eng	Modelling of Rough-Fuzzy Classifier	The paper reflects the trend of the past years which is based on the diffusion of various traditional approaches and methods to the way of tackling new problems, in this case to the classification. Two components of the computational intelligence are applied in a classification model. It means rough and fuzzy sets on the basis of which the data classification hybrid model is proposed. In the second part the current knowledge in the investigated field are summarized and briefly explained. The algorithm for uncertain data operations and conditioned rules generation is introduced too. We have brought in an original toolbox called RSTbox for data processing and automatic rules generation. Proposed model and toolbox are carried out in MATLAB, tested on more data files, and compared to others, already known classification methods.	Classification; rough sets theory; fuzzy sets theory; rules generation; hybrid model; evaluation