salso (version 0.2.5)

psm: Compute an Adjacency or Pairwise Similarity Matrix

Description

If only one sample is provided, this function computes an adjacency matrix, i.e., a binary matrix whose $(i,j)$ element is one if and only if elements $i$ and $j$ in the partition have the same cluster label. If multiple samples are provided (as rows of the x matrix), this function computes the $n$-by-$n$ matrix whose $(i,j)$ element gives the relative frequency (i.e., estimated probability) that items $i$ and $j$ are in the same subset (i.e., cluster). This is the mean of the adjacency matrices of the provided samples.

Usage

psm(x, nCores = 0)

Arguments

x

A $B$-by-$n$ matrix, where each of the $B$ rows represents a clustering of $n$ items using cluster labels. For clustering $b$, items $i$ and $j$ are in the same cluster if x[b,i] == x[b,j].

nCores

The number of CPU cores to use. A value of zero indicates to use all cores on the system.

Value

A $n$-by-$n$ symmetric matrix whose $(i,j)$ element gives the relative frequency that that items $i$ and $j$ are in the same subset (i.e., cluster).

Examples

# NOT RUN {
partition <- iris.clusterings[1,]
psm(partition)

dim(iris.clusterings)
# For examples, use 'nCores=1' per CRAN rules, but in practice omit this.
probs <- psm(iris.clusterings, nCores=1)
dim(probs)
probs[1:6, 1:6]

# }