On using genetic algorithm for initialising semi-supervised fuzzy c-means clustering
In a previous work, suitable initialisation techniques were incorporated with semi-supervised Fuzzy c-Means clustering (ssFCM) to improve clustering results on a trial and error basis. In this work, we present a single fully-automatic version of an existing semi-supervised Fuzzy c-means clustering f...
| Main Authors: | , |
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| Format: | Article |
| Published: |
Springer
2016
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| Subjects: | |
| Online Access: | https://eprints.nottingham.ac.uk/38397/ |