@Alias(value="de.lmu.ifi.dbs.elki.distance.distancefunction.SparseManhattanDistanceFunction") public class SparseManhattanDistanceFunction extends SparseLPNormDistanceFunction
SparseNumberVectors.
Manhattan distance is defined as:
\[ \text{Manhattan}(\vec{x},\vec{y}) := \sum_i |x_i-y_i| \]| Modifier and Type | Class and Description |
|---|---|
static class |
SparseManhattanDistanceFunction.Parameterizer
Parameterizer
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| Modifier and Type | Field and Description |
|---|---|
static SparseManhattanDistanceFunction |
STATIC
Static instance
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| Constructor and Description |
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SparseManhattanDistanceFunction()
Deprecated.
Use static instance instead.
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| Modifier and Type | Method and Description |
|---|---|
double |
distance(SparseNumberVector v1,
SparseNumberVector v2)
Computes the distance between two given DatabaseObjects according to this
distance function.
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double |
norm(SparseNumberVector v1)
Compute the norm of object obj.
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getInputTypeRestriction, isMetricclone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, waitinstantiateisSquared, isSymmetricpublic static final SparseManhattanDistanceFunction STATIC
@Deprecated public SparseManhattanDistanceFunction()
STATIC instead.public double distance(SparseNumberVector v1, SparseNumberVector v2)
PrimitiveDistanceFunctiondistance in interface PrimitiveDistanceFunction<SparseNumberVector>distance in class SparseLPNormDistanceFunctionv1 - first DatabaseObjectv2 - second DatabaseObjectpublic double norm(SparseNumberVector v1)
Normnorm in interface Norm<SparseNumberVector>norm in class SparseLPNormDistanceFunctionv1 - ObjectCopyright © 2019 ELKI Development Team. License information.