KMeansClusterCollectionDistortion Method

Calculates the average square distance from the data points to the nearest clusters' centroids.

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

Syntax

Copy

public double Distortion(
	double[][] data,
	int[] labels = null,
	double[] weights = null
)

Public Function Distortion ( 
	data As Double()(),
	Optional labels As Integer() = Nothing,
	Optional weights As Double() = Nothing
) As Double

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Parameters

data: Type: SystemDouble
The data.
labels (Optional): Type: SystemInt32
The labels.
weights (Optional): Type: SystemDouble
The weights.

Return Value

Type: Double
The average square distance from the data points to the nearest clusters' centroids.

Implements

ICentroidClusterCollectionTData, TCentroids, TClusterDistortion(TData, Int32, Double)

Remarks

The average distance from centroids can be used as a measure of the "goodness" of the clustering. The more the data are aggregated around the centroids, the less the average distance.

Reference

KMeansClusterCollection Class

Accord.MachineLearning Namespace

KMeansClusterCollectionAddLanguageSpecificTextSet("LSTA8B230BC_0?cpp=::|nu=.");Distortion Method

Parameters

Return Value

Implements

Reference

KMeansClusterCollectionDistortion Method