DocumentCode
1117318
Title
A Method of Using Cluster Analysis to Study Statistical Dependence in Multivariate Data
Author
Borucki, William J. ; Card, Don H. ; Lyle, Gilbert C.
Author_Institution
NASA Ames Research Center
Issue
12
fYear
1975
Firstpage
1183
Lastpage
1191
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.
Keywords
Clustering algorithms, data analysis, multivariate analysis, nonlinear data structures, pattern recognition.; Algorithm design and analysis; Clustering algorithms; Data analysis; Fluctuations; Gaussian distribution; Iris; Monte Carlo methods; Multidimensional systems; Statistical distributions; Testing; Clustering algorithms, data analysis, multivariate analysis, nonlinear data structures, pattern recognition.;
fLanguage
English
Journal_Title
Computers, IEEE Transactions on
Publisher
ieee
ISSN
0018-9340
Type
jour
DOI
10.1109/T-C.1975.224162
Filename
1672755
Link To Document