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Non-symmetrical factorial discriminant analysis for symbolic objects

✍ Scribed by Francesco Palumbo; Rosanna Verde


Publisher
John Wiley and Sons
Year
1999
Tongue
English
Weight
106 KB
Volume
15
Category
Article
ISSN
1524-1904

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✦ Synopsis


In this paper we propose a generalization of the factorial discriminant analysis (FDA) to complex data structures named Symbolic Objects. We assume that the a priori classes are de"ned by an equal number of intention symbolic objects. The paper proposes a three-step discrimination procedure. Symbolic data are coded in suitable numerical matrices, coded variables are transformed into canonical variables, symbolic objects are visualized building maximum covering area rectangles, with respect to the canonical variables. Referring to the graphical representation, geometrical rules are proposed in order to assign new objects to a a priori class on the basis of proximity measures.