cluster_agreement: Agreement between two partitions
In MosaiClusteR: An Umbrella Framework for Multi-Source and Multi-Omics Clustering
View source: R/utils-evaluation.R
cluster_agreement R Documentation
Agreement between two partitions
Description
Computes the adjusted Rand index (ARI), normalised mutual information (NMI)
and pairwise Jaccard between two label vectors of equal length.
Usage
cluster_agreement(a, b)
Arguments
a, b
Integer/character/factor label vectors of equal length.
Details
ARI rule of thumb: >0.90 excellent; 0.75-0.90 good;
0.50-0.75 moderate; <0.50 weak.
Value
A named numeric vector c(ARI, NMI, Jaccard).
Examples
cluster_agreement(c(1, 1, 2, 2), c(2, 2, 1, 1)) # identical up to relabel
MosaiClusteR documentation built on Oct. 25, 2026, 1:08 a.m.
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View source: R/utils-evaluation.R
| cluster_agreement | R Documentation |
Agreement between two partitions
Description
Computes the adjusted Rand index (ARI), normalised mutual information (NMI) and pairwise Jaccard between two label vectors of equal length.
Usage
cluster_agreement(a, b)
Arguments
a, b |
Integer/character/factor label vectors of equal length. |
Details
ARI rule of thumb: >0.90 excellent; 0.75-0.90 good;
0.50-0.75 moderate; <0.50 weak.
Value
A named numeric vector c(ARI, NMI, Jaccard).
Examples
cluster_agreement(c(1, 1, 2, 2), c(2, 2, 1, 1)) # identical up to relabel
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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