PRODUCTS
PURCHASE
FOR USERS
COMPANY
OUR SITES
DOCUMENTATION CENTER SEARCH
Mathematica
>
Distance and Dissimilarity Measures
>
Built-in
Mathematica
Symbol
Partitioning Data into Clusters
Tutorials »
|
JaccardDissimilarity
MatchingDissimilarity
SokalSneathDissimilarity
RogersTanimotoDissimilarity
RussellRaoDissimilarity
YuleDissimilarity
See Also »
|
Distance and Dissimilarity Measures
More About »
DiceDissimilarity
DiceDissimilarity
[
x
,
y
]
gives the dice dissimilarity between Boolean vectors
x
and
y
.
MORE INFORMATION
DiceDissimilarity
works for both
True
,
False
vectors and
0
,
1
vectors.
DiceDissimilarity
[
u
,
v
]
is equivalent to
(
n
10
+
n
01
)/(2
n
11
+
n
10
+
n
01
)
, 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)
Dice dissimilarity between two 0, 1 vectors:
In[1]:=
Out[1]=
Dice dissimilarity between two Boolean vectors:
In[1]:=
Out[1]=
Scope
(2)
Applications
(2)
Properties & Relations
(4)
SEE ALSO
JaccardDissimilarity
MatchingDissimilarity
SokalSneathDissimilarity
RogersTanimotoDissimilarity
RussellRaoDissimilarity
YuleDissimilarity
TUTORIALS
Partitioning Data into Clusters
MORE ABOUT
Distance and Dissimilarity Measures
New in 6
© 2008 Wolfram Research, Inc.
EXAMPLES
Basic Examples 
Scope 