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2 results

  • 21 - Classification

  • Jan Lepš, University of South Bohemia, Czech Republic, Petr Šmilauer, University of South Bohemia, Czech Republic
  • Book:
    Biostatistics with R
    Published online:
    18 September 2020
    Print publication:
    30 July 2020, pp 317-325

  • Summary

    After a general introduction to multivariate statistical analyses, we focus on describing the task of multivariate classification, distinguishing its non-hierarchical and hierarchical forms. Focusing on hierarchical agglomerative classification methods (cluster analysis), we highlight the important decisions that must be made regarding the measurement of dissimilarity (distance) among objects. Following this, we explain the construction of dendrograms representing this hierarchical classification. We also briefly mention divisive classification methods, focusing on the TWINSPAN method. The methods described in this chapter are accompanied by a carefully-explained guide to the R code needed for their use, in this case employing the cluster package.