randIndex_fast: Rand Index

In Jakob-Bach/FastTSDistances: Fast dissimilarity computations for time series

Description

Calculates the Rand Index of Rand (1971) to compare two cluster assignment vectors (external cluster validation). It is a value in (0,1], higher values indicating more similarity. The index can be corrected for similarity by chance as proposed by Hubert and Arabie (1985), then also possibly yielding negative results (if the similarity is worse than random assignment) while the maximum is still 1 (and values are usually positive).

Usage

randIndex_fast(pairCVIParams, normalize = FALSE)

Arguments

pairCVIParams	Output of link{pairCVIParameters} which has to be called with the two cluster assignment vector to be compared.
normalize	Should the Rand Index be corrected for chance? (Adjusted Rand Index as proposed by Hubert and Arabie (1985))

Value

The (Adjusted) Rand Index as double (at most 1 for identical clusterings, normal Rand Index greater than zero, adjusted one can also be negative).

References

Hubert, L. & Arabie, P. (1985). Comparing partitions. Journal of classification,2(1), 193-218.

Rand, W. M. (1971). Objective criteria for the evaluation of clustering methods. Journal of the American Statistical association, 66(336), 846-850.

Wu, J., Xiong, H. & Chen, J. (2009). Adapting the right measures for k-means clustering. In Proceedings of the 15th acm sigkdd international conference on knowledge discovery and data mining (pp. 877-886). ACM.

See Also

Other External Cluster Validity Indices: conditionalEntropy_fast, fowlkesMallows_fast, pairCVIParameters_fast, phi_fast, purity_fast, vanDongen_fast

Jakob-Bach/FastTSDistances documentation built on May 13, 2019, 1:15 p.m.