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 , 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

open allclose all

## Basic Examples(1)

Distance matrix for a list of numbers:

## Options(1)

### DistanceFunction(1)

Distance matrix using ManhattanDistance:

Wolfram Research (2007), DistanceMatrix, Wolfram Language function, https://reference.wolfram.com/language/HierarchicalClustering/ref/DistanceMatrix.html.

#### Text

Wolfram Research (2007), DistanceMatrix, Wolfram Language function, https://reference.wolfram.com/language/HierarchicalClustering/ref/DistanceMatrix.html.

#### CMS

Wolfram Language. 2007. "DistanceMatrix." Wolfram Language & System Documentation Center. Wolfram Research. https://reference.wolfram.com/language/HierarchicalClustering/ref/DistanceMatrix.html.

#### APA

Wolfram Language. (2007). DistanceMatrix. Wolfram Language & System Documentation Center. Retrieved from https://reference.wolfram.com/language/HierarchicalClustering/ref/DistanceMatrix.html

#### BibTeX

@misc{reference.wolfram_2024_distancematrix, author="Wolfram Research", title="{DistanceMatrix}", year="2007", howpublished="\url{https://reference.wolfram.com/language/HierarchicalClustering/ref/DistanceMatrix.html}", note=[Accessed: 19-July-2024 ]}

#### BibLaTeX

@online{reference.wolfram_2024_distancematrix, organization={Wolfram Research}, title={DistanceMatrix}, year={2007}, url={https://reference.wolfram.com/language/HierarchicalClustering/ref/DistanceMatrix.html}, note=[Accessed: 19-July-2024 ]}