Fuzzy K-means clustering with missing values
Fuzzy K-means clustering algorithm is a popular approach for exploring the structure of a set of patterns, especially when the clusters are overlapping or fuzzy. However, the fuzzy K-means clustering algorithm cannot be applied when the real-life data contain missing values. In many cases, the numbe...
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| Main Authors: | , |
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| Format: | text |
| Language: | English |
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Institutional Knowledge at Singapore Management University
2001
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| Online Access: | https://ink.library.smu.edu.sg/sis_research/3020 |
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| Institution: | Singapore Management University |
| Language: | English |