Publication Date:
2011-08-16
Description:
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.
Keywords:
STATISTICS AND PROBABILITY
Type:
IEEE Transactions on Computers; C-24; Dec. 197
Format:
text