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The Tutorial of Principal Component Analysis, Hierarchical Clustering, and Multidimensional Scaling Wenshan Wang Multi-dimensional Scaling (MDS) “Multi-dimensional scaling (MDS) is a method that represents measurements of similarity (or dissimilarity) among pairs of objects as distances between points of a low-dimensional multidimensional space.” ------------ Ingwer Borg and Patrick J.F. Groenen From Purposes o
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  The Tutorial of Principal Component Analysis, Hierarchical Clustering, and Multidimensional Scaling Wenshan Wang  Multi-dimensional Scaling (MDS) “Multi -dimensional scaling (MDS) is a method that represents measurements of similarity (or dissimilarity) among pairs of objects as distances between points of a low-dimensional multidimensional space. ”  ------------ Ingwer Borg and Patrick J.F. Groenen From <<Modern Multidimensional Scaling: Theory and Applications>>  Purposes of using MDS ã Exploratory technique ã Testing Structural Hypotheses ã Similarity Judgments  Principal Component Analysis (PCA) ã Principal Component Analysis is a method of identifying the pattern of data set by a much smaller number of “new” variables, named as principal components.
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