  This report discusses two new indices for comparing clusterings of a set of
points. The motivation for looking at new ways for comparing clusterings stems
from the fact that the existing clustering indices are based on set cardinality
alone and do not consider the positions of data points. The new indices,
namely, the Random Walk index (RWI) and Variation of Information with Neighbors
(VIN), are both inspired by the clustering metric Variation of Information
(VI). VI possesses some interesting theoretical properties which are also
desirable in a metric for comparing clusterings. We define our indices and
discuss some of their explored properties which appear relevant for a
clustering index. We also include the results of these indices on clusterings
of some example data sets.
