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In this type of clustering the objects are allowed to belong to
more then one cluster and has a degree of membership assigned from [0,1].
Algorithm
- Select an initial partition. Repeat steps 2 to 4 until the cluster
memberships stabilize.
- Computer the membership functions.
- Compute the criterion function.
- Reclassify patterns to improve the value of the criterion function.
Fuzzy clustering is useful in cases where the clusters are
touching or overlapping.
Miranda Maria Irene
Thu Apr 1 15:43:18 IST 1999