Common clustering algorithms

I. Lee, J. Yang

    Research output: Chapter in Book / Conference PaperChapter

    57 Citations (Scopus)

    Abstract

    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.
    Original languageEnglish
    Title of host publicationComprehensive Chemometrics: Chemical and Biochemical Data Analysis
    EditorsSteven D. Brown, Roma Tauler, Beata Walczak
    Place of PublicationU.K.
    PublisherElsevier
    Pages577-618
    Number of pages42
    ISBN (Electronic)9780444527011
    ISBN (Print)9780444527028
    DOIs
    Publication statusPublished - 2009

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