plot_similarity: Plot similarity objective by cluster

In m-Py/anticlust: Subset Partitioning via Anticlustering

Plot similarity objective by cluster

Description

Plot similarity objective by cluster

Usage

plot_similarity(x, groups)

Arguments

x

The data input. Can be one of two structures: (1) A data matrix where rows correspond to elements and columns correspond to features (a single numeric feature can be passed as a vector). (2) An N x N matrix dissimilarity matrix; can be an object of class dist (e.g., returned by dist or as.dist) or a matrix where the entries of the upper and lower triangular matrix represent the pairwise dissimilarities.

groups

A grouping vector of length N, usually the output of matching.

Details

Plots the sum of pairwise distances by group.

Value

The diversity (sum of distances) by group.

Author(s)

Martin Papenberg [e-mail]

See Also

diversity_objective

Examples

# Match elements and plot similarity by match
N <- 100
lds <- data.frame(f1 = rnorm(N), f2 = rnorm(N))
pairs <- matching(lds, p = 2)
plot_similarity(lds, pairs)

m-Py/anticlust documentation built on April 13, 2025, 11:17 p.m.