The Distance Matrix platform computes various measures of distance or dissimilarity between the observations (rows) of a data set. Methods include Euclidean (default), Manhattan, Jaccard, Gower, Bray-Curtis, Binary, and Hamming. These proximity measures are stored as a square matrix in an output data set. The number of rows and columns in the output matrix equals the number of observations in the input data set. If there are By groups, an output matrix is computed for each group, and the size is determined by the maximum number of observations in any By group.
The output distance matrix can be used for hierarchical clustering and for heatmap visualizations, depending on your needs.
Note: The Distance Matrix platform is available only in JMP Pro.