C# Class KdKeys.DataMining.Clustering.KMeans.KMeansParallel

This class implement a KMeans clustering algorithm

Public Methods

Method	Description
ClusterDataSet ( ClusterCollection clusters, double data ) : ClusterCollection	Seperates a dataset into clusters or groups with similar characteristics
ClusterDataSet ( int clusterCount, double data ) : ClusterCollection	Seperates a dataset into clusters or groups with similar characteristics
ClusterDataSetRandomSeeding ( int k, double data ) : ClusterCollection	Seperates a dataset into clusters or groups with similar characteristics
ClusterMean ( double cluster ) : double[]	Calculates The Mean Of A Cluster OR The Cluster Center
ClusterPartialDataSet ( ClusterCollection clusters, double data, int start, int count ) : int[]
EuclideanDistance ( double X, double Y ) : double	Calculates the Euclidean Distance Measure between two data points
KMeansParallel ( ) : System
ManhattanDistance ( double X, double Y ) : double	Calculates the Manhattan Distance Measure between two data points
RandomSeeding ( int k, double data ) : ClusterCollection
Serialize ( System myObject, string writeToXmlPath ) : bool	Saves or Serializes a Cluster Collection To an Xml file

Seperates a dataset into clusters or groups with similar characteristics

public ClusterDataSet ( ClusterCollection clusters, double data ) : ClusterCollection
clusters	ClusterCollection	A collection of data clusters
data	double	An array containing data to b eclustered
return	ClusterCollection

Seperates a dataset into clusters or groups with similar characteristics

public ClusterDataSet ( int clusterCount, double data ) : ClusterCollection
clusterCount	int	The number of clusters or groups to form
data	double	An array containing data that will be clustered
return	ClusterCollection

Seperates a dataset into clusters or groups with similar characteristics

public ClusterDataSetRandomSeeding ( int k, double data ) : ClusterCollection
k	int
data	double	An array containing data that will be clustered
return	ClusterCollection

Calculates The Mean Of A Cluster OR The Cluster Center

public ClusterMean ( double cluster ) : double[]
cluster	double	/// A two-dimensional array containing a dataset of numeric values ///
return	double[]

public ClusterPartialDataSet ( ClusterCollection clusters, double data, int start, int count ) : int[]
clusters	ClusterCollection
data	double
start	int
count	int
return	int[]

Calculates the Euclidean Distance Measure between two data points

public EuclideanDistance ( double X, double Y ) : double
X	double	An array with the values of an object or datapoint
Y	double	An array with the values of an object or datapoint
return	double

public KMeansParallel ( ) : System
return	System

Calculates the Manhattan Distance Measure between two data points

public ManhattanDistance ( double X, double Y ) : double
X	double	An array with the values of an object or datapoint
Y	double	An array with the values of an object or datapoint
return	double

public RandomSeeding ( int k, double data ) : ClusterCollection
k	int
data	double
return	ClusterCollection

Saves or Serializes a Cluster Collection To an Xml file

public static Serialize ( System myObject, string writeToXmlPath ) : bool
myObject	System	A serializable object to be persisted to an Xml file
writeToXmlPath	string	The location of the Xml file tha will contain serialized data
return	bool