@Alias(value="de.lmu.ifi.dbs.elki.distance.distancefunction.SparseManhattanDistanceFunction") public class SparseManhattanDistanceFunction extends SparseLPNormDistanceFunction
SparseNumberVector
s.
Manhattan distance is defined as:
\[ \text{Manhattan}(\vec{x},\vec{y}) := \sum_i |x_i-y_i| \]Modifier and Type | Class and Description |
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static class |
SparseManhattanDistanceFunction.Parameterizer
Parameterizer
|
Modifier and Type | Field and Description |
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static SparseManhattanDistanceFunction |
STATIC
Static instance
|
Constructor and Description |
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SparseManhattanDistanceFunction()
Deprecated.
Use static instance instead.
|
Modifier and Type | Method and Description |
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double |
distance(SparseNumberVector v1,
SparseNumberVector v2)
Computes the distance between two given DatabaseObjects according to this
distance function.
|
double |
norm(SparseNumberVector v1)
Compute the norm of object obj.
|
getInputTypeRestriction, isMetric
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
instantiate
isSquared, isSymmetric
public static final SparseManhattanDistanceFunction STATIC
@Deprecated public SparseManhattanDistanceFunction()
STATIC
instead.public double distance(SparseNumberVector v1, SparseNumberVector v2)
PrimitiveDistanceFunction
distance
in interface PrimitiveDistanceFunction<SparseNumberVector>
distance
in class SparseLPNormDistanceFunction
v1
- first DatabaseObjectv2
- second DatabaseObjectpublic double norm(SparseNumberVector v1)
Norm
norm
in interface Norm<SparseNumberVector>
norm
in class SparseLPNormDistanceFunction
v1
- ObjectCopyright © 2019 ELKI Development Team. License information.