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DOCUMENTATION CENTER SEARCH
New to
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Find your learning path
»
Mathematica
>
OBSOLETE MATHEMATICA SYMBOL
Partitioning Data into Clusters
Tutorials »
|
ManhattanDistance
EuclideanDistance
SquaredEuclideanDistance
BrayCurtisDistance
CanberraDistance
CornerNeighbors
See Also »
ChebyshevDistance
As of
Mathematica
7,
is superseded by
ChessboardDistance
.
gives the Chebyshev or sup norm distance between vectors
u
and
v
.
MORE INFORMATION
is equivalent to
Max
[
Abs
[
u
-
v
]]
.
»
EXAMPLES
CLOSE ALL
Basic Examples
(2)
The Chebyshev distance between two vectors:
Chebyshev distance between numeric vectors:
The Chebyshev distance between two vectors:
In[1]:=
Out[1]=
Chebyshev distance between numeric vectors:
In[1]:=
Out[1]=
Scope
(2)
Compute the distance between any vectors of equal length:
Compute the distance between vectors of any precision:
Applications
(2)
Cluster data using Chebyshev distance:
Demonstrate the triangle inequality:
Properties & Relations
(4)
Chebyshev distance is the maximum of absolute differences:
is equivalent to a
Norm
of a difference:
is less than or equal to
ManhattanDistance
:
is less than or equal to
EuclideanDistance
:
SEE ALSO
ManhattanDistance
EuclideanDistance
SquaredEuclideanDistance
BrayCurtisDistance
CanberraDistance
CornerNeighbors
TUTORIALS
Partitioning Data into Clusters
New in 6