DocumentCode
1109282
Title
A Two-Dimensional Display for the Classification of Multivariate Data
Author
Fukunaga, Keinosuke ; Olsen, D.R.
Author_Institution
IEEE
Issue
8
fYear
1971
Firstpage
917
Lastpage
923
Abstract
The properties of a two-dimensional display whose coordinates are the Euclidean distances from two points in a multivariate space are presented. When used in conjunction with three linear normalization procedures, this display is a useful tool in both supervised and unsupervised classification problems. In addition, some geometric structure is preserved by this mapping. Examples using well-known Iris data are presented to demonstrate the display characteristics.
Keywords
Clustering, dimensionality reduction, display mapping, iterative operation, multivariate data analysis, optimal decision boundaries, pattern recognition, supervised classification, unsupervised classification.; Computer displays; Data analysis; Data structures; Density functional theory; Euclidean distance; Iris; Nonlinear distortion; Pattern recognition; Two dimensional displays; Vectors; Clustering, dimensionality reduction, display mapping, iterative operation, multivariate data analysis, optimal decision boundaries, pattern recognition, supervised classification, unsupervised classification.;
fLanguage
English
Journal_Title
Computers, IEEE Transactions on
Publisher
ieee
ISSN
0018-9340
Type
jour
DOI
10.1109/T-C.1971.223371
Filename
1671964
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