GaussianMixtureModel Properties 
The GaussianMixtureModel type exposes the following members.
Name  Description  

Clusters 
Gets the collection of clusters currently modeled by the
clustering algorithm.
 
ComputeLabels 
Gets or sets whether cluster labels should be computed
at the end of the learning iteration. Setting to False
might save a few computations in case they are not necessary.
 
ComputeLogLikelihood 
Gets or sets whether the loglikelihood should be computed
at the end of the learning iteration. Setting to False
might save a few computations in case they are not necessary.
 
Gaussians 
Gets the Gaussian components of the mixture model.
 
Initializations 
Gets or sets how many random initializations to try.
Default is 3.
 
Iterations 
Gets how many iterations have been performed in the last call
to Compute(Double).
 
LogLikelihood 
Gets the loglikelihood of the model at the last iteration.
 
MaxIterations 
Gets or sets the maximum number of iterations to
be performed by the method. If set to zero, no
iteration limit will be imposed. Default is 0.
 
Options 
Gets or sets the fitting options for the component
Gaussian distributions of the mixture model.
 
ParallelOptions 
Gets or sets the parallelization options for this algorithm.
(Inherited from ParallelLearningBase.)  
Token 
Gets or sets a cancellation token that can be used
to cancel the algorithm while it is running.
(Inherited from ParallelLearningBase.)  
Tolerance 
Gets or sets the convergence criterion for the
ExpectationMaximization algorithm. Default is 1e3.
 
UseLogarithm 
Gets or sets whether to make computations using the log
domain. This might improve accuracy on large datasets.
