On classification with missing data using rough-neuro-fuzzy systems
نویسنده
چکیده
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.
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ورودعنوان ژورنال:
- Applied Mathematics and Computer Science
دوره 20 شماره
صفحات -
تاریخ انتشار 2010