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Variable Selection in Artefact Compositional Studies
Author(s) -
Baxter M. J.,
Jackson C. M.
Publication year - 2001
Publication title -
archaeometry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.716
H-Index - 67
eISSN - 1475-4754
pISSN - 0003-813X
DOI - 10.1111/1475-4754.00017
Subject(s) - selection (genetic algorithm) , variable (mathematics) , feature selection , principal component analysis , computer science , archaeological science , epistemology , econometrics , artificial intelligence , history , mathematics , archaeology , philosophy , mathematical analysis
In artefact compositional studies, the selection of variables to use in analysis is unavoidable. Given this ubiquity, surprisingly little attention has been paid to ways in which variables might be selected. After arguing the case for the importance of variable selection, two systematic approaches to making a choice, which have had little or no application in archaeometry, are discussed and illustrated. One, based on the use of principal components, is appropriate if structure in the data is not known. The other, based on the use of classification trees, is applicable when there are known or assumed groups in the data.