Do.boolean.membership.matrix: Function to compute and build up a pairwise boolean...

In mosclust: Model Order Selection for Clustering

Function to compute and build up a pairwise boolean membership matrix.

Description

It computes the pairwise membership matrix for a given clustering. The number of rows is equal to the number of columns (the number of examples). The element m_{ij} is set to 1 if the examples i and j belong to the same cluster, otherwise to 0. This function may be used also with clusterings that do not define strictly a partition of the data and using diferent number of clusters for each clustering.

Usage

Do.boolean.membership.matrix(cl, dim.M, examplelabels)

Arguments

cl	a clustering (list of vectors defining a clustering)
dim.M	dimension of the similarity matrix (number of examples)
examplelabels	labels of the examples drawn from the original data

Value

the pairwise boolean membership square matrix.

Author(s)

Giorgio Valentini [e-mail]

Examples

library("clusterv")
library("stats")
# Synthetic data set generation (3 clusters with 20 examples for each cluster)
M <- generate.sample3(n=20, m=2)
# k-means clustering with 3 clusters
r<-kmeans(t(M), c=3, iter.max = 1000);
# this function is implemented in the clusterv package:
cl <- Transform.vector.to.list(r$cluster); 
# generation of boolean membership square matrix:
B <- Do.boolean.membership.matrix(cl, 60, 1:60)

mosclust documentation built on June 8, 2025, 11:23 a.m.