On classification with missing data using rough-neuro-fuzzy systems

• Autorzy: Robert K. Nowicki
• Języki publikacji: EN

Abstrakty

EN

The paper presents a new approach to fuzzy classification in the case of missing data. Rough-fuzzy sets are incorporated into logical type neuro-fuzzy structures and a rough-neuro-fuzzy classifier is derived. Theorems which allow determining the structure of the rough-neuro-fuzzy classifier are given. Several experiments illustrating the performance of the roughneuro-fuzzy classifier working in the case of missing features are described.

Słowa kluczowe

EN

fuzzy sets; rough sets; neuro-fuzzy architectures; classification; missing data

• Wydawca: University of Zielona Gora Press
• Czasopismo: International Journal of Applied Mathematics and Computer Science
• Rocznik: 2010
• Tom: 20
• Numer: 1
• Strony: 55-67

Daty

wydano

2010

otrzymano

2009-02-07

poprawiono

2009-07-21

Twórcy

autor

Robert K. Nowicki

• Institute of Information Technology, Academy of Management (SWSPiZ), ul. Sienkiewicza 9, 90-113 Łódź, Poland
• Department of Computer Engineering, Częstochowa University of Technology, ul. Armii Krajowej 36, 42-200 Częstochowa, Poland

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Identyfikatory

DOI

10.2478/v10006-010-0004-8