Cluster AnalysisHeinemann Educational [for] the Social Science Research Council, 1974 - 122 páginas A review of clustering techniques; A discussion of the problems of cluster analysis; An empirical investigation of some methods of cluster analysis; Using cluster analysis techniques in practice: some guide lines. |
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algorithm applied assignment attempt average Biometrics bivariate normal population bivariate observations C₁ C₂ centroid Chapter classification cluster analysis techniques clustering criterion clustering methods clustering techniques considered correlation covariance matrix criteria defined dendrogram dimensional discriminant function discussed distance matrix distance measures entities Euclidean distance example factor analysis Friedman & Rubin fused Gitman given hierarchical clustering hierarchical techniques individuals initial investigator Jardine Kruskal local optimum mathematical maximum likelihood mean vector method of cluster metric minimization minimum spanning tree mixtures Mode analysis multidimensional scaling multivariate normal distributions number of clusters number of groups obtained parameters partition points principal components analysis priori problem procedure psychiatric Psychol Research sample scores set of data shown in Fig Sibson similarity and distance similarity coefficient single linkage clustering Sneath Sokal solutions space statist structure suggested sum of squares taxonomy tion trace types variance-covariance matrix Ward's method weight Wishart