Abstract
This work deals with the extension of classical linear regression to symbolic data and constitutes a continuation of previous papers from Billard and Diday on linear regression with interval and histogram-valued data. In this paper, we present a method for regression with taxonomic variables. Taxonomic variables are variables organized in a tree with several levels of generality. For example, the towns are aggregated up to their regions, the regions are aggregated up to their country.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Afonso, F., Billard, L., and Diday, E. (2004). “Régression Linéaire Symbolique avec Variables Taxonomiques,” in Actes des IVèmes Journées d’Extraction et Gestion des Connaissance, EGC Clermont-Ferrand 2004, eds. Hébrail and al., RNTI-E-2, Vol. 1, pp. 205–210.
Afonso, F., Billard, L., and Diday, E. (2003). “Extension des Méthodes de Régression Linéaire aux cas des Variables Symboliques Taxonomiques et Hiérarchiques,” Actes des XXXVèmes journées de Statistique, SFDS Lyon 2003, Vol. 1, pp. 89–92.
Billard, L., and Diday, E. (2003). “From the Statistics of Data to the Statistics of Knowledge: Symbolic Data Analysis,” Journal of the American Statistical Association, 98, 470–487
Billard, L., and Diday, E. (2002). “Symbolic Regression Analysis,” in Classification, Clustering and Data Analysis, eds. H.-H. Bock et al., Berlin: SpringerVerlag, pp. 281–288.
Billard, L., and Diday, E. (2000). “Regression Analysis for Interval-Valued Data,” in Data Analysis, Classification and Related Methods, eds. H. Kiers et al., Berlin: Springer-Verlag, pp. 369–374.
Bock, H.-H., and Diday E. (2000). Analysis Data Sets: Exploratory Methods for Extracting Statistical Information from Complex Data, Springer-Verlag, Berlin.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2004 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Afonso, F., Billard, L., Diday, E. (2004). Symbolic Linear Regression with Taxonomies. In: Banks, D., McMorris, F.R., Arabie, P., Gaul, W. (eds) Classification, Clustering, and Data Mining Applications. Studies in Classification, Data Analysis, and Knowledge Organisation. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17103-1_40
Download citation
DOI: https://doi.org/10.1007/978-3-642-17103-1_40
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22014-5
Online ISBN: 978-3-642-17103-1
eBook Packages: Springer Book Archive