A Method of Using Cluster Analysis to Study Statistical Dependence in Multivariate Data

Authors:
W. J. Borucki;D. H. Card;G. C. Lyle
Affiliations:
NASA Ames Research Center;-;-
Venue:
IEEE Transactions on Computers
Year:
1975

Citing 3
Cited 0

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Abstract

A technique is presented that uses both cluster analysis and a Monte Carlo significance test of clusters to discover associations between variables in multidimensional data. The method is applied to an example of a noisy function in three-dimensional space, to a sample from a mixture of three bivariate normal distributions, and to the well-known Fisher's Iris data.