HIERARCHICAL SYMBOLIC CLUSTERING FOR DISTRIBUTION VALUED DATA
2010 Volume 22 Issue 2 Pages 83-89
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2010 Volume 22 Issue 2 Pages 83-89
We propose a hierarchical clustering in the framework of Symbolic Data Analysis (SDA). SDA was proposed by Diday at the end of the 1980s and is a new approach for analysing huge and complex data. In SDA, an observation is described by not only numerical values but also "higher-level units"; sets, intervals, distributions, etc. Most SDA works have dealt with only intervals as the descriptions. In this paper, we propose a hierarchical clustering for distribution valued data and show its effectiveness through a numerical simulation.
