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Distance and Dissimilarity Measures
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Partitioning Data into Clusters
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JaccardDissimilarity
DiceDissimilarity
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Discrete & Integer Data
Distance and Dissimilarity Measures
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MatchingDissimilarity
MatchingDissimilarity
[
u
,
v
]
gives the matching dissimilarity between Boolean vectors
u
and
v
.
MORE INFORMATION
MatchingDissimilarity
works for both
True
,
False
vectors and
vectors.
MatchingDissimilarity
[
u
,
v
]
is equivalent to
(
n
10
+
n
01
)/
Length
[
x
]
, where
n
ij
is the number of corresponding pairs of elements in
u
and
v
respectively equal to
i
and
j
.
EXAMPLES
CLOSE ALL
Basic Examples
(2)
Matching dissimilarity between two Boolean vectors:
In[1]:=
Out[1]=
The elements can also be
True
and
False
:
In[1]:=
Out[1]=
Scope
(2)
Applications
(2)
Properties & Relations
(5)
SEE ALSO
JaccardDissimilarity
DiceDissimilarity
SokalSneathDissimilarity
RogersTanimotoDissimilarity
RussellRaoDissimilarity
YuleDissimilarity
TUTORIALS
Partitioning Data into Clusters
MORE ABOUT
Discrete & Integer Data
Distance and Dissimilarity Measures
Logic & Boolean Algebra
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vectors.
EXAMPLES
Basic Examples 
Scope 