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A comparison of simulated annealing algorithms for variable selection in principal component analysis and discriminant analysis

✍ Scribed by Brusco, Michael J.

Book ID
122230140
Publisher
Elsevier Science
Year
2014
Tongue
English
Weight
645 KB
Volume
77
Category
Article
ISSN
0167-9473

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Principal component analysis is a useful method for analysing data-matrices. By analysing separate class models, i.e. disjoint principal component modelling as in the SIMCA or FCVPC programs (developed for supervised and unsupervised principal component analysis respectively), the principal componen