GmmVbem: Variational Bayes EM algorithm for Gaussian Mixture Model.
In jlin-vt/SML: Statistical Machine Learning
Description
Usage
Arguments
Value
See Also
Description
Variational Bayes EM algorithm for Gaussian Mixture Model.
Usage
1
Arguments
x
training data of size DxN.
mix
gmm model initialize with netlab's GmmVBEM function.
PriorPar
structure containing priors.
options
options for maxIter, threshold etc. etc.
D
the dimension.
N
the number of Data points.
Value
a list of objects:
L likelihood function.
m centers of clusters.
See Also
http://www.cs.ubc.ca/~murphyk/Software/VBEMGMM/index.html
jlin-vt/SML documentation built on Dec. 5, 2019, 2:05 a.m.
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Description Usage Arguments Value See Also
Description
Variational Bayes EM algorithm for Gaussian Mixture Model.
Usage
1 |
Arguments
x |
training data of size DxN. |
mix |
gmm model initialize with netlab's GmmVBEM function. |
PriorPar |
structure containing priors. |
options |
options for maxIter, threshold etc. etc. |
D |
the dimension. |
N |
the number of Data points. |
Value
a list of objects: L likelihood function. m centers of clusters.
See Also
http://www.cs.ubc.ca/~murphyk/Software/VBEMGMM/index.html
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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