A Clustering Preserving Transformation for k-Means Algorithm Output
| Autor: | Kłopotek, Mieczysław A. |
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| Rok vydání: | 2022 |
| Předmět: | |
| Druh dokumentu: | Working Paper |
| Popis: | This note introduces a novel clustering preserving transformation of cluster sets obtained from $k$-means algorithm. This transformation may be used to generate new labeled data{}sets from existent ones. It is more flexible that Kleinberg axiom based consistency transformation because data points in a cluster can be moved away and datapoints between clusters may come closer together. Comment: 14 pages, 5 figures; the paper extends the method of consistency transformation discussed in arXiv:2202.06015. arXiv admin note: substantial text overlap with arXiv:2202.06015 |
| Databáze: | arXiv |
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