Description Usage Arguments Details References Examples
View source: R/registry-seed.R
nmfSeed
lists and retrieves NMF seeding methods.
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name |
access key of a seeding method stored in registry.
If missing, |
... |
extra arguments used for internal calls |
exact |
a logical that indicates if the access key should be matched exactly or partially. |
Currently the internal registry contains the following seeding methods,
which may be specified to the function nmf
via its argument
seed
using their access keys:
The entries of each factors are drawn from a uniform distribution over [0, max(x)], where $x$ is the target matrix.
Nonnegative Double Singular Value Decomposition.
The basic algorithm contains no randomization and is based on two SVD processes, one approximating the data matrix, the other approximating positive sections of the resulting partial SVD factors utilising an algebraic property of unit rank matrices.
It is well suited to initialise NMF algorithms with sparse factors. Simple practical variants of the algorithm allows to generate dense factors.
Reference: Boutsidis and Gallopoulos (2008)
Uses the result of an Independent Component Analysis (ICA)
(from the fastICA
package).
Only the positive part of the result are used to initialise the factors.
Fixed seed.
This method allows the user to manually provide initial values for both matrix factors.
Boutsidis C, Gallopoulos E (2008). “SVD based initialization: A head start for nonnegative matrix factorization.” _Pattern Recognition_, *41*(4), 1350-1362. ISSN 00313203, doi: 10.1016/j.patcog.2007.09.010 (URL: https://doi.org/10.1016/j.patcog.2007.09.010).
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