Noun
mutual information (usually uncountable, plural mutual informations)
(information theory) A measure of the entropic (informational) correlation between two random variables.
Mutual information
I
(
X
;
Y
)
{\displaystyle I(X;Y)}
between two random variables
X
{\displaystyle X}
and
Y
{\displaystyle Y}
is what is left over when their mutual conditional entropies
H
(
Y
|
X
)
{\displaystyle H(Y|X)}
and
H
(
X
|
Y
)
{\displaystyle H(X|Y)}
are subtracted from their joint entropy
H
(
X
,
Y
)
{\displaystyle H(X,Y)}
. It can be given by the formula
I
(
X
;
Y
)
=
−
∑
x
∑
y
p
X
,
Y
(
x
,
y
)
log
b
p
X
,
Y
(
x
,
y
)
p
X
|
Y
(
x
|
y
)
p
Y
|
X
(
y
|
x
)
{\displaystyle I(X;Y)=-\sum _{x}\sum _{y}p_{X,Y}(x,y)\log _{b}{p_{X,Y}(x,y) \over p_{X|Y}(x|y)p_{Y|X}(y|x)}}
.
A basic property of this form of conditional entropy is that: : Mutual information (transinformation) Mutual information measures the amount of information that can be obtained about one random variable by observing another. Source: Internet