ISSN:
1433-3058
Keywords:
Keywords:Feature evaluation index ; Feature selection; Radial Basis Function network
Source:
Springer Online Journal Archives 1860-2000
Topics:
Computer Science
,
Mathematics
Notes:
Abstract. A new method of feature selection using a Radial Basis Function network is described. The parameters of the radial basis function network, in general, form a compact description of class structures. The intraclass and interclass distances are expressed in terms of the parameters of the trained network, and two different feature evaluation indices are derived from these distances. The effectiveness of the algorithm is demonstrated on Iris and speech data, and a comparative study is provided with several existing techniques.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1007/s005210050035
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