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Adaptation of interval PCA to symbolic histogram variables

Makosso Kallyth, Sun; Diday, Edwin (2012), Adaptation of interval PCA to symbolic histogram variables, Advances in Data Analysis and Classification, 6, 2, p. 147-159. http://dx.doi.org/10.1007/s11634-012-0108-0

Type
Article accepté pour publication ou publié
Date
2012
Journal name
Advances in Data Analysis and Classification
Volume
6
Number
2
Publisher
Springer
Pages
147-159
Publication identifier
http://dx.doi.org/10.1007/s11634-012-0108-0
Metadata
Show full item record
Author(s)
Makosso Kallyth, Sun
Diday, Edwin
Abstract (EN)
This paper is an adaptation of symbolic interval Principal Component Analysis (PCA) to histogram data. We proposed two methodologies. The first one involved three steps: the coding of bins of histogram, the ordinary PCA of means of variables and the representation of dispersion of symbolic observations we call concepts. For the representation of dispersion of these concepts we proposed the transformation of histograms into intervals. Then, we suggest the projection of the hypercubes or the interval lengths associated to each concept on the principal axes of the ordinary PCA of means. In the second methodology, we proposed the use of the three previous steps with the angular transformation.
Subjects / Keywords
Symbolic histogram variable; Hypercube; Tchebychev inequality; Angular transformation; Procrustean analysis

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