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Variation of information
Encyclopedia
The variation of information (
) is a measure of the distance between two clusterings (partitions of elements
).
s)
and
where
,
,
. Then the variation of information between two clusterings is:
![](http://image.absoluteastronomy.com/images/formulas/9/1/4911505-7.gif)
where
is entropy of
and
is mutual information
between
and
.
This is completely equivalent to the shared information distance.
![](http://image.absoluteastronomy.com/images/formulas/9/1/4911505-1.gif)
Partition of a set
In mathematics, a partition of a set X is a division of X into non-overlapping and non-empty "parts" or "blocks" or "cells" that cover all of X...
).
Definition
Suppose we have two clusterings (a division of a set into several subsetSubset
In mathematics, especially in set theory, a set A is a subset of a set B if A is "contained" inside B. A and B may coincide. The relationship of one set being a subset of another is called inclusion or sometimes containment...
s)
![](http://image.absoluteastronomy.com/images/formulas/9/1/4911505-2.gif)
![](http://image.absoluteastronomy.com/images/formulas/9/1/4911505-3.gif)
![](http://image.absoluteastronomy.com/images/formulas/9/1/4911505-4.gif)
![](http://image.absoluteastronomy.com/images/formulas/9/1/4911505-5.gif)
![](http://image.absoluteastronomy.com/images/formulas/9/1/4911505-6.gif)
![](http://image.absoluteastronomy.com/images/formulas/9/1/4911505-7.gif)
where
![](http://image.absoluteastronomy.com/images/formulas/9/1/4911505-8.gif)
![](http://image.absoluteastronomy.com/images/formulas/9/1/4911505-9.gif)
![](http://image.absoluteastronomy.com/images/formulas/9/1/4911505-10.gif)
Mutual information
In probability theory and information theory, the mutual information of two random variables is a quantity that measures the mutual dependence of the two random variables...
between
![](http://image.absoluteastronomy.com/images/formulas/9/1/4911505-11.gif)
![](http://image.absoluteastronomy.com/images/formulas/9/1/4911505-12.gif)
This is completely equivalent to the shared information distance.