Faq convergence of PARAFAC: Difference between revisions
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imported>Lyle (Created page with "===Issue:=== Convergence of PARAFAC. How much variation between models is expected a particular PARAFAC is fit multiple times with the same settings? ===Possible Solutions:=...") |
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If repeatedly fitted models are not identical in fit, it is an indication that your problem is very complex. It can be because you use too many components, because the real components are too similar within the signal-to-noise or because your data do not follow a low-rank trilinear model. | If repeatedly fitted models are not identical in fit, it is an indication that your problem is very complex. It can be because you use too many components, because the real components are too similar within the signal-to-noise or because your data do not follow a low-rank trilinear model. | ||
'''Still having problems? Please contact our helpdesk at [mailto:helpdesk@eigenvector.com helpdesk@eigenvector.com]''' | |||
[[Category:FAQ]] | [[Category:FAQ]] | ||
Latest revision as of 11:00, 5 December 2018
Issue:
Convergence of PARAFAC. How much variation between models is expected a particular PARAFAC is fit multiple times with the same settings?
Possible Solutions:
Correctly converged models can vary in the loadings (e.g. permutation of components) but the fit should be exactly the same (e.g. as expressed by the sum of the squared residuals).
If repeatedly fitted models are not identical in fit, it is an indication that your problem is very complex. It can be because you use too many components, because the real components are too similar within the signal-to-noise or because your data do not follow a low-rank trilinear model.
Still having problems? Please contact our helpdesk at helpdesk@eigenvector.com