Probabilistic and More General Uncertainty-Based (e.g., Fuzzy) Approaches to Crisp Clustering Explain the Empirical Success of the K-Sets Algorithm (Q5015710)
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scientific article; zbMATH DE number 7442002
| Language | Label | Description | Also known as |
|---|---|---|---|
| English | Probabilistic and More General Uncertainty-Based (e.g., Fuzzy) Approaches to Crisp Clustering Explain the Empirical Success of the K-Sets Algorithm |
scientific article; zbMATH DE number 7442002 |
Statements
Probabilistic and More General Uncertainty-Based (e.g., Fuzzy) Approaches to Crisp Clustering Explain the Empirical Success of the K-Sets Algorithm (English)
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9 December 2021
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clustering
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K-sets algorithm
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probabilistic uncertainty
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fuzzy uncertainty
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