Abstract
In the previous chapters, several methods of data classification and regression were presented. Reference was made to the dimensionality ratio problem, which led us to describe and use variable selection techniques. The problem with these techniques is that they cannot detect hidden variables in the data, responsible for interesting data variability. In the present chapter we describe techniques that allow us to analyse the data structure with the dual objective of dimensional reduction and improved data interpretation.
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© 2003 Springer-Verlag Berlin Heidelberg
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Marques de Sá, J.P. (2003). Data Structure Analysis. In: Applied Statistics Using SPSS, STATISTICA and MATLAB. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-05804-6_8
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DOI: https://doi.org/10.1007/978-3-662-05804-6_8
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-662-05806-0
Online ISBN: 978-3-662-05804-6
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