HierarchicalClusteringSimilarityDistanceMeasure Enumeration

TIBCO Spotfire 6.5 API Reference

Represents a Similarity or a Distance Measure that can be used in Hierarchical Clustering.

Namespace: Spotfire.Dxp.Data.Computations.Clustering
Assembly: Spotfire.Dxp.Data (in Spotfire.Dxp.Data.dll) Version: 14.10.7525.5058 (14.10.7525.5058)

Syntax

C++

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[SerializableAttribute]
[PersistenceVersionAttribute(6, 0)]
public enum HierarchicalClusteringSimilarityDistanceMeasure

[SerializableAttribute]
[PersistenceVersionAttribute(6, 0)]
public enum HierarchicalClusteringSimilarityDistanceMeasure

Members

Member name	Value	Description
Correlation	1	Correlation, Pearson's correlation, Pearson's r. Subtract the mean value of the coordinates, normalize and take the scalar product.
UnsignedCorrelation	2	Unsigned correlation is absolut value of correlation.
CosineCorrelation	3	Normalized scalar product without subtracting the mean value.
Tanimoto	4	Tanimoto Coefficient, normally only used for binary valued data.
Euclidean	5	The ordinary distance in n-dimensional space.
CityBlock	6	City block distance, Manhattan distance, L1 distance, rectilinear distance.
SquareEuclidean	7	The Euclidean distance squared.
HalfSquareEuclidean	8	The Euclidean distance squared and divided by 2; mandatory for Ward's clustering method.

Remarks

Similarities with ranges: Correlation [1, -1], UnsignedCorrelation [1, 0], CosineCorrelation [1, -1], Tanimoto [1, -1/3] ([1, 0] on binary input). Similarities has 1 as most similar value and lower value for less similar.

Distances all have range [0, float.MaxValue]: Euclidean, CityBlock, SquaredEuclidean, HalfSquaredEuclidean. Distances has 0 as smallest distance and higher value for more distant pairs of objects.

Version Information

Supported in: 6.5, 6.0, 5.5, 5.0, 4.5