Rand indices

Rand index is a measure of the similarity between two data clusterings. From a mathematical standpoint, Rand index is related to the accuracy, but is applicable even when class labels are not used.

References:

Lawrence Hubert and Phipps Arabie (1985). Comparing partitions. Journal of Classification 2 (1): 193–218

Meila, Marina (2003). Comparing Clusterings by the Variation of Information. Learning Theory and Kernel Machines: 173–187.

This package provides the randindex function that implements several metrics:

randindex(c1, c2)

Compute the tuple of indices (Adjusted Rand index, Rand index, Mirkin’s index, Hubert’s index) between two assignments.

Parameters:
  • c1 – The assignment vector for the first clustering.
  • c2 – The assignment vector for the second clustering.
Returns:

tuple of indices.
randindex(R, c0)

This method takes R, an instance of ClusteringResult, as input, and computes the tuple of indices (see above) where c0 is the corresponding assignment vector.

randindex(R1, R2)

This method takes R1 and R2 (both are instances of ClusteringResult) and computes the tuple of indices (see above) between them.