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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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Published in:Archaeometry Vol. 48; no. 4; pp. 671 - 695
Main Author: Baxter, M. J.
Format: Article
Published: Wiley-Blackwell Nov2006
Subjects:
Archaeological surveying
Pattern perception
Supervised study
Principal components analysis
Cluster analysis (Statistics)
Discriminant analysis
Glass industry
Logistic regression analysis
Online Access:View this record in EBSCOhost