private void constructor(int components)
{
ComputeLabels = true;
ComputeLogLikelihood = true;
Tolerance = 1e-3;
Initializations = 3;
MaxIterations = 0;
UseLogarithm = true;
Options = new Statistics.Distributions.Fitting.NormalOptions();
// Initialize the model using the created objects.
this.clusters = new GaussianClusterCollection(components);
}
private void constructor(int components)
{
// Create the object-oriented structure to hold
// information about mixture model components.
var clusterList = new List <GaussianCluster>(components);
for (int i = 0; i < components; i++)
{
clusterList.Add(new GaussianCluster(this, i));
}
// Initialize the model using the created objects.
this.clusters = new GaussianClusterCollection(this, clusterList);
}
/// <summary>
/// Initializes a new instance of the <see cref="GaussianMixtureModel"/> class.
/// </summary>
///
/// <param name="components">
/// The number of clusters in the clusterization problem. This will be
/// used to set the number of components in the mixture model.</param>
///
public GaussianMixtureModel(int components)
{
if (components <= 0)
{
throw new ArgumentOutOfRangeException("components",
"The number of components should be greater than zero.");
}
// Create the object-oriented structure to hold
// information about mixture model components.
var clusterList = new List <GaussianCluster>(components);
for (int i = 0; i < components; i++)
{
clusterList.Add(new GaussianCluster(this, i));
}
// Initialize the model using the created objects.
this.clusters = new GaussianClusterCollection(clusterList);
}
