KullbackLeiblerDivergenceReverseAsymmetricDistance (ELKI: Environment for DeveLoping KDD-Applications Supported by Index-Structures)

java.lang.Object
- elki.distance.AbstractNumberVectorDistance
- - elki.distance.probabilistic.KullbackLeiblerDivergenceReverseAsymmetricDistance

All Implemented Interfaces:

Distance<NumberVector>, NumberVectorDistance<NumberVector>, PrimitiveDistance<NumberVector>
```
@Reference(authors="S. Kullback",
           title="Information theory and statistics",
           booktitle="",
           bibkey="books/dover/Kullback59")
@Alias("kli")
public class KullbackLeiblerDivergenceReverseAsymmetricDistance
extends AbstractNumberVectorDistance
```
Kullback-Leibler divergence, also known as relative entropy, information deviation or just KL-distance (albeit asymmetric).
\[KL_R(\vec{x},\vec{y}):=\sum\nolimits_i y_i\log\tfrac{y_i}{x_i} = KL(\vec{y},\vec{x})\]
This version has the arguments reversed, see KullbackLeiblerDivergenceAsymmetricDistance for the "forward" version.
For a symmetric version, see JeffreyDivergenceDistance.
Reference:
S. Kullback
Information theory and statistics

Since:

0.6.0

Author:

Erich Schubert

Nested Class Summary

Nested Classes
Modifier and Type Class Description

static class KullbackLeiblerDivergenceReverseAsymmetricDistance.Par
Parameterization class, using the static instance.

Field Summary

Fields
Modifier and Type Field Description

static KullbackLeiblerDivergenceReverseAsymmetricDistance STATIC
Static instance.

Constructor Summary

Constructors
Constructor Description

KullbackLeiblerDivergenceReverseAsymmetricDistance()
Deprecated.
Use static instance!

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method	Description
`double`	`distance(NumberVector v1, NumberVector v2)`	Computes the distance between two given vectors according to this distance function.
`boolean`	`equals(java.lang.Object obj)`
`int`	`hashCode()`
`boolean`	`isSymmetric()`	Is this function symmetric?
`java.lang.String`	`toString()`

Methods inherited from class elki.distance.AbstractNumberVectorDistance
dimensionality, dimensionality, dimensionality, dimensionality, dimensionality, dimensionality, dimensionality, dimensionality, getInputTypeRestriction

Methods inherited from class java.lang.Object
clone, finalize, getClass, notify, notifyAll, wait, wait, wait

Methods inherited from interface elki.distance.Distance
isMetric, isSquared

Methods inherited from interface elki.distance.PrimitiveDistance
instantiate

- Field Detail
  - STATIC
```
public static final KullbackLeiblerDivergenceReverseAsymmetricDistance STATIC
```
    Static instance. Use this!
- Constructor Detail
  - KullbackLeiblerDivergenceReverseAsymmetricDistance
```
@Deprecated
public KullbackLeiblerDivergenceReverseAsymmetricDistance()
```
    Deprecated.
    Use static instance!
    
    Constructor for the Kullback-Leibler divergence.
- Method Detail
  - distance
```
public double distance(NumberVector v1,
                       NumberVector v2)
```
    Description copied from interface: NumberVectorDistance
    
    Computes the distance between two given vectors according to this distance function.
    
    Parameters:
    
    v1 - first vector
    
    v2 - second vector
    
    Returns:
    
    the distance between two given vectors according to this distance function
  - isSymmetric
```
public boolean isSymmetric()
```
    Description copied from interface: Distance
    
    Is this function symmetric?
    
    Returns:
    
    true when symmetric
  - toString
```
public java.lang.String toString()
```
    Overrides:
    
    toString in class java.lang.Object
  - equals
```
public boolean equals(java.lang.Object obj)
```
    Overrides:
    
    equals in class java.lang.Object
  - hashCode
```
public int hashCode()
```
    Overrides:
    
    hashCode in class java.lang.Object