An entropy-based density peaks clustering algorithm for mixed type data employing fuzzy neighborhood
Most clustering algorithms rely on the assumption that data simply contains numerical values. In fact, however, data sets containing both numerical and categorical attributes are ubiquitous in real-world tasks, and effective grouping of such data is an important yet challenging problem. Currently mo...
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| Vydané v: | Knowledge-based systems Ročník 133; s. 294 - 313 |
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| Hlavní autori: | , , , , |
| Médium: | Journal Article |
| Jazyk: | English |
| Vydavateľské údaje: |
Amsterdam
Elsevier B.V
01.10.2017
Elsevier Science Ltd |
| Predmet: | |
| ISSN: | 0950-7051, 1872-7409 |
| On-line prístup: | Získať plný text |
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