A REVIEW OF SUPERVISED AND UNSUPERVISED PATTERN RECOGNITION IN ARCHAEOMETRY.

Principal component, cluster and discriminant analysis are multivariate statistical methods that are widely used in archaeometry. They are examples of what are known in some literatures as unsupervised and supervised learning methods. Over the past 20 years or so, a wide variety of other learning me...

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Publicado en:	Archaeometry Vol. 48; no. 4; pp. 671 - 695
Autor principal:	Baxter, M. J.
Formato:	Artículo
Publicado:	Wiley-Blackwell Nov2006
Materias:	Archaeological surveying Pattern perception Supervised study Principal components analysis Cluster analysis (Statistics) Discriminant analysis Glass industry Logistic regression analysis
Acceso en línea:	Ver este registro en EBSCOhost