An optimal and stable algorithm for clustering numerical data
In the conventional k-means framework, seeding is the first step toward optimization before the objects are clustered. In random seeding, two main issues arise: the clustering results may be less than optimal and different clustering results may be obtained for every run. In real-world applications,...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021
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| Series: | Algorithms
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| Subjects: | |
| Online Access: | View Fulltext in Publisher View in Scopus |