Geometrical models to explore and represent asymmetric proximity data are usually classified in two classes: distance models and scalar product models. In this paper we focalize on scalar product models, emphasizing some relationships and showing possibilities to incorporate external information that can help the analysis of proximities between rows and columns of data matrices. In particular it is 7 pointed out how some of these model apply to the analysis of skew-symmetry with external information.
Bove, G. (2010). Models for asymmetry in proximity data. In Data Analysis and Classification. Studies in Classification, Data Analysis, and Knowledge Organization (pp. 79-84). BERLIN HEIDELBERG : Springer-Verlag [10.1007/978-3-642-03739-9 9].
Models for asymmetry in proximity data
BOVE, Giuseppe
2010-01-01
Abstract
Geometrical models to explore and represent asymmetric proximity data are usually classified in two classes: distance models and scalar product models. In this paper we focalize on scalar product models, emphasizing some relationships and showing possibilities to incorporate external information that can help the analysis of proximities between rows and columns of data matrices. In particular it is 7 pointed out how some of these model apply to the analysis of skew-symmetry with external information.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
