Fuzzy feature selection

✍ Scribed by M. Ramze Rezaee; B. Goedhart; B.P.F. Lelieveldt; J.H.C. Reiber

• Book ID: 104160435
• Publisher: Elsevier Science
• Year: 1999
• Tongue: English
• Weight: 132 KB
• Volume: 32
• Category: Article
• ISSN: 0031-3203
• DOI: 10.1016/s0031-3203(99)00005-9

✦ Synopsis

In fuzzy classi"er systems the classi"cation is obtained by a number of fuzzy If}Then rules including linguistic terms such as Low and High that fuzzify each feature. This paper presents a method by which a reduced linguistic (fuzzy) set of a labeled multi-dimensional data set can be identi"ed automatically. After the projection of the original data set onto a fuzzy space, the optimal subset of fuzzy features is determined using conventional search techniques. The applicability of this method has been demonstrated by reducing the number of features used for the classi"cation of four real-world data sets. This method can also be used to generate an initial rule set for a fuzzy neural network.