Nonmetric Multidimensional Scaling As a Data-Mining Tool: New Algorithm and New Targets

Y. H. Taguchi, Yoshitsugu Oono

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

We have explained our efficient and maximally nonmetric multidimensional scaling method (nMDS) applicable to very large data sets and have illustrated how it can be effectively used to extract qualitative features (structures and patterns) hidden in the data set. Examples of genomic, phylogenetic and ecological data analyses illustrate the versatility of the (large scale) use of nMDS. Certain criteria to evaluate the goodness of the nMDS results are also proposed.

Original languageEnglish (US)
Title of host publicationAdvances in Chemical Physics
PublisherWiley-Blackwell
Pages315-351
Number of pages37
Volume130
ISBN (Electronic)9780471712534
ISBN (Print)0471711586, 9780471711582
DOIs
StatePublished - May 12 2005

Keywords

  • Data mining
  • Large samples
  • Multi-variate analysis
  • Nonmetric multidimensional scaling

ASJC Scopus subject areas

  • Chemistry(all)

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  • Cite this

    Taguchi, Y. H., & Oono, Y. (2005). Nonmetric Multidimensional Scaling As a Data-Mining Tool: New Algorithm and New Targets. In Advances in Chemical Physics (Vol. 130, pp. 315-351). Wiley-Blackwell. https://doi.org/10.1002/0471712531.ch18