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Advisor(s)
Abstract(s)
Cluster analysis or classification usually concerns a set of exploratory multivariate data analysis
methods and techniques for grouping either a set of statistical data units or the associated set of descriptive
variables, into clusters of similar and, hopefully, well separated elements. In this work we refer to
an extension of this paradigm to generalized three-way data representations and particularly to classification
of interval variables. Such approach appears to be especially useful in large data bases, mostly in
a data mining context. A health sciences case study is partially discussed.
Description
© 2014 Cises This work is distributed with License Creative Commons Attribution-Non commercial-No derivatives 4.0 International (CC BY-BC-ND 4.0)
Keywords
Three-way data Interval variable Cluster analysis of variables Similarity coefficient Hierarchical clustering model
Pedagogical Context
Citation
TPM Vol. 21, No. 4, December 2014 – 435-447 – Special Issue
Publisher
CISES