Abstract
An adaptive algorithm is presented for fuzzy clustering of data. Partitioning is fuzzified by addition of an entropy term to objective functions. The proposed method produces more convex membership functions than those given by the fuzzy c- means algorithm.
Original language | English |
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Pages (from-to) | 390-391 |
Number of pages | 2 |
Journal | IEICE Transactions on Information and Systems |
Volume | E76-D |
Issue number | 3 |
Publication status | Published - Mar 1 1993 |
All Science Journal Classification (ASJC) codes
- Software
- Hardware and Architecture
- Computer Vision and Pattern Recognition
- Electrical and Electronic Engineering
- Artificial Intelligence