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Dynamic generation of prototypes with self-organizing feature maps for classifier design

✍ Scribed by Arijit Laha; Nikhil R. Pal


Publisher
Elsevier Science
Year
2001
Tongue
English
Weight
161 KB
Volume
34
Category
Article
ISSN
0031-3203

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✦ Synopsis


We propose a new scheme for designing a nearest-prototype classi"er using Kohonen's self-organizing feature map (SOFM). The net starts with the minimum number of prototypes which is equal to the number of classes. Then on the basis of the classi"cation performance, new prototypes are generated dynamically. The algorithm merges similar prototypes and deletes less signi"cant prototypes. If prototypes are deleted or new prototypes appear then they are "ne tuned using Kohonen's SOFM algorithm with the winner-only update strategy. This adaptation continues until the system satis"es a termination condition. The classi"er has been tested with several well-known data sets and the results obtained are quite satisfactory.