Nvalidate: Difference between revisions

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===Inputs ===
===Inputs ===


* '''x'''
* '''x''' multi-way array to be modeled
* '''ncomp' number of components to be modeled.  Set ncomp to [1:4] to test one -to four compenent models if using parafac.  If using tucker, instead set ncomp to [2 2 2; 4 5 4] to check from 2 to 4/5 components depending on mode.
 
* '''method''' Either 'parafac' or 'tucker'


===Outputs ===
===Outputs ===

Revision as of 12:16, 2 August 2016

Purpose

Validate the number PARAFAC or Tucker components.


Synopsis

result = nvalidate(x,ncomp,method,options);
nvalidate(result,x) %Plot earlier results
nvalidate(x,1:3,'parafac')  % Validate 1-3 component PARAFAC models
nvalidate(x,[1 1 1;3 3 3],'tucker') % validate [1 1 1] to [3 3 3] comp Tucker3 models


Inputs

  • x multi-way array to be modeled
  • ncomp' number of components to be modeled. Set ncomp to [1:4] to test one -to four compenent models if using parafac. If using tucker, instead set ncomp to [2 2 2; 4 5 4] to check from 2 to 4/5 components depending on mode.
  • method Either 'parafac' or 'tucker'

Outputs

The outputs of the nvalidate function are returned as a struct with the following fields

  • ssq The sum-squared error. What to look for: look for sudden changes as in a Scree-Plot(often difficult) and look for sudden increase in number of local minima (replicate points for a number of components are not identical). This is often a good indication that noise is being modeled.
  • models Cell of models where element {f,r} is the r'th model replicate fit with f components