An exploration of improvements to semi-supervised fuzzy c-means clustering for real-world biomedical data
This thesis explores various detailed improvements to semi-supervised learning (using labelled data to guide clustering or classification of unlabelled data) with fuzzy c-means clustering (a ‘soft’ clustering technique which allows data patterns to be assigned to multiple clusters using membership v...
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| Main Author: | |
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| Format: | Thesis (University of Nottingham only) |
| Language: | English |
| Published: |
2014
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| Online Access: | http://eprints.nottingham.ac.uk/14232/ http://eprints.nottingham.ac.uk/14232/1/correction_noblue.pdf |
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