Common Clustering Algorithms

This chapter surveys common clustering algorithms widely used in the data mining community in light of chemometrics. It starts with taxonomy of clustering algorithms, and discusses two common clustering approaches – partitioning clustering and hierarchical clustering – in detail. Several variants of these clustering methods are presented and their strengths and weaknesses are addressed. This chapter continues to overview hybrid clustering approaches combining partitioning clustering and hierarchical clustering, and concludes with a quick overview on constrained clustering.

• Publication year

  2020

• Venue

  Comprehensive Chemometrics

• Publication date

  Unknown publication date

• Fields of study

  Chemistry, Computer Science

• Identifiers
  DOI 10.1016/B978-044452701-1.00064-8
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

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• No concepts are published for this paper.

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