publication . Other literature type . Article . 1997

PARAFAC. Tutorial and applications

Rasmus Bro;
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  • Published: 01 Oct 1997
  • Publisher: Elsevier BV
Abstract
Abstract This paper explains the multi-way decomposition method PARAFAC and its use in chemometrics. PARAFAC is a generalization of PCA to higher order arrays, but some of the characteristics of the method are quite different from the ordinary two-way case. There is no rotation problem in PARAFAC, and e.g., pure spectra can be recovered from multi-way spectral data. One cannot as in PCA estimate components successively as this will give a model with poorer fit, than if the simultaneous solution is estimated. Finally scaling and centering is not as straightforward in the multi-way case as in the two-way case. An important advantage of using multi-way methods inst...
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Subjects
arXiv: Computer Science::Numerical Analysis
free text keywords: Multi way analysis, Principal component regression, Chemometrics, Matlab code, Machine learning, computer.software_genre, computer, Mathematics, Scaling, Decomposition method (constraint satisfaction), Spectral data, Artificial intelligence, business.industry, business, Algorithm, Regression
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