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Paper details
Number 1 - March 2010
Volume 20 - 2010
On classification with missing data using rough-neuro-fuzzy systems
Robert K. Nowicki
Abstract
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 rough-neuro-fuzzy classifier working in the case of missing features are described.
Keywords
fuzzy sets, rough sets, neuro-fuzzy architectures, classification, missing data