Computes the variation of information for two classification vectors.
VarInf(id1, id2)
first partitioning vector.
second partitioning vector.
Returns the variation of information. It is equal to 0 if and only if two classification vectors are identical.
Meila, M. (2006) ``Comparing clusterings - an information based distance'', Journal of Multivariate Analysis, 98, 873-895.
ClassProp, and RandIndex.
ClassProp
RandIndex
# NOT RUN { <!-- %\dontrun{ --> # } # NOT RUN { id1 <- c(rep(1, 50), rep(2,100)) id2 <- rep(1:3, each = 50) VarInf(id1, id2) # } # NOT RUN { <!-- %} --> # }
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