Description Usage Arguments Value Author(s) References See Also Examples
computes an estimate of the best rank-R PARAFAC model of a tensor X with nonnegative constraints on the factors. This version uses the Lee & Seung multiplicative updates from their NMF algorithm. Translated from cp_nmu.m : MATLAB Tensor Toolbox
1 |
X |
is a sparse tensor (a LIST containing subs, vals and size) |
R |
The rank of the factorization |
opts |
a list containing the options for the algorithm like maxiters:maximum iterations, tol:tolerance .. etc. |
P |
the factorization of X as a LIST representing Kruskal Tensor (lambda and u) |
Uinit |
the initial solution |
stats |
statistics about the solution like the running time of each step and the error. |
fit |
fraction explained by the model. |
Abdelmoneim Amer Desouki
-Brett W. Bader, Tamara G. Kolda and others. MATLAB Tensor Toolbox, Version [v3.0]. Available online at https://www.tensortoolbox.org, 2015.
-Lee, Daniel D., and H. Sebastian Seung. "Algorithms for non-negative matrix factorization." In Advances in neural information processing systems, pp. 556-562. 2001.
cp_apr
serial_parCube
rescal
cp_als
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