agreement: Agreement-based Measures for Clustering

In stream: Infrastructure for Data Stream Mining

Agreement-based Measures for Clustering

Description

Calculates the agreement between two partitions, typically the known actual cluster labels and the predicted cluster labels.

Usage

agreement(predicted, actual, method = "cRand", na_as_cluster = TRUE)

Arguments

predicted	a vector with predicted cluster labels.
actual	the known cluster labels (ground truth).
method	the used method (see clue::cl_agreement()).
na_as_cluster	logical; should NA labels (noise points) be considered its own cluster?

Details

This convenience function is an interface to clue::cl_agreement(). See methods in that man page for a list of available methods. A measure typically used for clustering is the corrected Rand index (also called adjusted Rand index). Numbers close to 1 indicate a very good agreement.

References

Hornik K (2005). A CLUE for CLUster Ensembles. Journal of Statistical Software, 14(12). doi: 10.18637/jss.v014.i12

Examples

# Perfect agreement (1 and 2 are just switched)
actual <- c(2, 2, 1, 3, 2, NA)
predicted <- c(1, 1, 2, 3, 1, NA)
agreement(actual, predicted)

# No agreement
predicted <- sample(predicted)
agreement(actual, predicted)

stream documentation built on March 7, 2023, 6:09 p.m.