VarInf: Variation of Information
In MixSim: Simulating Data to Study Performance of Clustering Algorithms
VarInf R Documentation
Variation of Information
Description
Computes the variation of information for two classification vectors.
Usage
VarInf(id1, id2)
Arguments
id1
first partitioning vector.
id2
second partitioning vector.
Value
Returns the variation of information. It is equal to 0 if and only if two classification vectors are identical.
Author(s)
Volodymyr Melnykov, Wei-Chen Chen, and Ranjan Maitra.
References
Meila, M. (2006) “Comparing clusterings - an information based distance”, Journal of Multivariate Analysis, 98, 873-895.
See Also
ClassProp, and RandIndex.
Examples
id1 <- c(rep(1, 50), rep(2,100))
id2 <- rep(1:3, each = 50)
VarInf(id1, id2)
MixSim documentation built on Sept. 11, 2024, 9:08 p.m.
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| VarInf | R Documentation |
Variation of Information
Description
Computes the variation of information for two classification vectors.
Usage
VarInf(id1, id2)
Arguments
id1 |
first partitioning vector. |
id2 |
second partitioning vector. |
Value
Returns the variation of information. It is equal to 0 if and only if two classification vectors are identical.
Author(s)
Volodymyr Melnykov, Wei-Chen Chen, and Ranjan Maitra.
References
Meila, M. (2006) “Comparing clusterings - an information based distance”, Journal of Multivariate Analysis, 98, 873-895.
See Also
ClassProp, and RandIndex.
Examples
id1 <- c(rep(1, 50), rep(2,100))
id2 <- rep(1:3, each = 50)
VarInf(id1, id2)
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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