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HierarchicalClustering`

HierarchicalClustering`

DistanceMatrix

As of Version 10.3, DistanceMatrix is built into the Wolfram System.

DistanceMatrix[list]

gives a matrix of distances or dissimilarities between the elements of list.

Details and Options

To use DistanceMatrix, you first need to load the Hierarchical Clustering Package using Needs["HierarchicalClustering`"].
The elements of list can be numeric lists, matrices, or tensors, lists of Boolean elements, or strings. All data elements must have the same dimensions.
DistanceMatrix returns a symmetric matrix suitable for use by DirectAgglomerate.
The method used to compute dissimilarities can be selected with the DistanceFunction option.
With the default setting DistanceFunction->Automatic, DistanceMatrix uses the square of EuclideanDistance for numeric data, JaccardDissimilarity for Boolean data, and EditDistance for string data.
The setting for DistanceFunction can be any distance or dissimilarity function or a pure function f defining a distance between two values.

Examples

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Basic Examples (1)

Distance matrix for a list of numbers:

Options (1)

DistanceFunction (1)

Distance matrix using ManhattanDistance:

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