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CvInvokeKmeans Method
http://www.emgu.com
Implements k-means algorithm that finds centers of cluster_count clusters and groups the input samples around the clusters. On output labels(i) contains a cluster index for sample stored in the i-th row of samples matrix

Namespace: Emgu.CV
Assembly: Emgu.CV.World (in Emgu.CV.World.dll) Version: 3.1.0.2282 (3.1.0.2282)
Syntax
public static double Kmeans(
	IInputArray data,
	int k,
	IOutputArray bestLabels,
	MCvTermCriteria termcrit,
	int attempts,
	KMeansInitType flags,
	IOutputArray centers = null
)

Parameters

data
Type: Emgu.CVIInputArray
Floating-point matrix of input samples, one row per sample
k
Type: SystemInt32
Number of clusters to split the set by.
bestLabels
Type: Emgu.CVIOutputArray
Output integer vector storing cluster indices for every sample
termcrit
Type: Emgu.CV.StructureMCvTermCriteria
Specifies maximum number of iterations and/or accuracy (distance the centers move by between the subsequent iterations)
attempts
Type: SystemInt32
The number of attempts. Use 2 if not sure
flags
Type: Emgu.CV.CvEnumKMeansInitType
Flags, use 0 if not sure
centers (Optional)
Type: Emgu.CVIOutputArray
Pointer to array of centers, use IntPtr.Zero if not sure

Return Value

Type: Double

[Missing <returns> documentation for "M:Emgu.CV.CvInvoke.Kmeans(Emgu.CV.IInputArray,System.Int32,Emgu.CV.IOutputArray,Emgu.CV.Structure.MCvTermCriteria,System.Int32,Emgu.CV.CvEnum.KMeansInitType,Emgu.CV.IOutputArray)"]

See Also