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Distance and Dissimilarity Measures
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Partitioning Data into Clusters
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Distance and Dissimilarity Measures
New in 6.0: Mathematics & Algorithms
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CorrelationDistance
CorrelationDistance
[
u
,
v
]
gives the correlation coefficient distance between vectors
u
and
v
.
MORE INFORMATION
CorrelationDistance
[
u
,
v
]
is equivalent to
1-(
u
-
Mean
[
u
]).(
v
-
Mean
[
v
])/(
Norm
[
u
-
Mean
[
u
]]
Norm
[
v
-
Mean
[
v
]])
.
»
EXAMPLES
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Basic Examples
(2)
The correlation distance between two vectors:
In[1]:=
Out[1]=
Correlation distance between numeric vectors:
In[1]:=
Out[1]=
Scope
(2)
Applications
(1)
Properties & Relations
(3)
SEE ALSO
CosineDistance
TUTORIALS
Partitioning Data into Clusters
MORE ABOUT
Distance and Dissimilarity Measures
New in 6.0: Mathematics & Algorithms
New in 6
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