GaussianClusterCollectionGaussianCluster Class

Gaussian Mixture Model cluster.

Inheritance Hierarchy

SystemObject
  Accord.MachineLearningClusterGaussianClusterCollection, Double, GaussianClusterCollectionGaussianCluster
    Accord.MachineLearningCentroidClusterGaussianClusterCollection, Double, IMixtureComponentMultivariateNormalDistribution, GaussianClusterCollectionGaussianCluster
      Accord.MachineLearningGaussianClusterCollectionGaussianCluster

Namespace: Accord.MachineLearning
Assembly: Accord.MachineLearning (in Accord.MachineLearning.dll) Version: 3.8.0

Syntax

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[SerializableAttribute]
public class GaussianCluster : CentroidCluster<GaussianClusterCollection, double[], IMixtureComponent<MultivariateNormalDistribution>, GaussianClusterCollectionGaussianCluster>, 
	IMixtureComponent<MultivariateNormalDistribution>

<SerializableAttribute>
Public Class GaussianCluster
	Inherits CentroidCluster(Of GaussianClusterCollection, Double(), IMixtureComponent(Of MultivariateNormalDistribution), GaussianClusterCollectionGaussianCluster)
	Implements IMixtureComponent(Of MultivariateNormalDistribution)

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The GaussianClusterCollectionGaussianCluster type exposes the following members.

Constructors

	Name	Description
	GaussianClusterCollectionGaussianCluster	Initializes a new instance of the GaussianClusterCollectionGaussianCluster class

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Properties

	Name	Description
	Centroid	Gets the cluster's centroid. (Inherited from CentroidClusterTCollection, TData, TCentroid, TCluster.)
	Coefficient	Gets the cluster's coefficient component.
	Component	Gets the component distribution.
	Covariance	Gets the clusters' variance-covariance matrices.
	Index	Gets the label for this cluster. (Inherited from ClusterTCollection, TData, TCluster.)
	Mean	Gets the mean vector associated with this cluster.
	Owner	Gets the collection to which this cluster belongs to. (Inherited from ClusterTCollection, TData, TCluster.)
	Proportion	Gets the proportion of samples contained in this cluster. (Inherited from ClusterTCollection, TData, TCluster.)
	Variance	Gets the variance vector associated with this cluster.

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Methods

	Name	Description
	Deviance	Gets the deviance of the points in relation to the cluster.
	Distortion	Computes the distortion of the cluster, measured as the average distance between the cluster points and its centroid. (Inherited from CentroidClusterTCollection, TData, TCentroid, TCluster.)
	Equals	Determines whether the specified object is equal to the current object. (Inherited from Object.)
	Finalize	Allows an object to try to free resources and perform other cleanup operations before it is reclaimed by garbage collection. (Inherited from Object.)
	GetHashCode	Serves as the default hash function. (Inherited from Object.)
	GetType	Gets the Type of the current instance. (Inherited from Object.)
	Likelihood	Gets the probability density function of the underlying Gaussian probability distribution evaluated in point x.
	LogLikelihood	Gets the probability density function of the underlying Gaussian probability distribution evaluated in point x.
	MemberwiseClone	Creates a shallow copy of the current Object. (Inherited from Object.)
	ToDistribution	Gets a copy of the normal distribution associated with this cluster.
	ToString	Returns a string that represents the current object. (Inherited from Object.)

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Extension Methods

	Name	Description
	HasMethod	Checks whether an object implements a method with the given name. (Defined by ExtensionMethods.)
	IsEqual	Compares two objects for equality, performing an elementwise comparison if the elements are vectors or matrices. (Defined by Matrix.)
	To(Type)	Overloaded. Converts an object into another type, irrespective of whether the conversion can be done at compile time or not. This can be used to convert generic types to numeric types during runtime. (Defined by ExtensionMethods.)
	ToT	Overloaded. Converts an object into another type, irrespective of whether the conversion can be done at compile time or not. This can be used to convert generic types to numeric types during runtime. (Defined by ExtensionMethods.)

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Remarks

This class contains information about a Gaussian cluster found during a GaussianMixtureModel estimation. Clusters are often contained within a GaussianClusterCollection.

Reference

Accord.MachineLearning Namespace

Accord.MachineLearningGaussianMixtureModel

Accord.MachineLearningGaussianClusterCollection

GaussianClusterCollectionAddLanguageSpecificTextSet("LSTBCDF1851_0?cpp=::|nu=.");GaussianCluster Class

Reference

GaussianClusterCollectionGaussianCluster Class