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

java.lang.Object
- elki.distance.AbstractNumberVectorDistance
- - elki.distance.correlation.SquaredPearsonCorrelationDistance

All Implemented Interfaces:

Distance<NumberVector>, NumberVectorDistance<NumberVector>, PrimitiveDistance<NumberVector>
```
public class SquaredPearsonCorrelationDistance
extends AbstractNumberVectorDistance
```
Squared Pearson correlation distance function for feature vectors.
The squared Pearson correlation distance is computed from the Pearson correlation coefficient \(r\) as: \(1-r^2\). Hence, possible values of this distance are between 0 and 1.
The distance between two vectors will be low (near 0), if their attribute values are dimension-wise strictly positively or negatively correlated. For features with uncorrelated attributes, the distance value will be high (near 1).

Since:

0.3

Author:

Arthur Zimek

Nested Class Summary

Nested Classes
Modifier and Type Class Description

static class SquaredPearsonCorrelationDistance.Par
Parameterization class.

Field Summary

Fields
Modifier and Type Field Description

static SquaredPearsonCorrelationDistance STATIC
Static instance.

Constructor Summary

Constructors
Constructor Description

SquaredPearsonCorrelationDistance()
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`	`isSquared()`	Squared distances, that would become metric after square root.
`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, isSymmetric

Methods inherited from interface elki.distance.PrimitiveDistance
instantiate

- Field Detail
  - STATIC
```
public static final SquaredPearsonCorrelationDistance STATIC
```
    Static instance.
- Constructor Detail
  - SquaredPearsonCorrelationDistance
```
@Deprecated
public SquaredPearsonCorrelationDistance()
```
    Deprecated.
    use static instance!
    
    Constructor - use STATIC instead.
- 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
  - isSquared
```
public boolean isSquared()
```
    Description copied from interface: Distance
    
    Squared distances, that would become metric after square root.
    E.g. squared Euclidean.
    
    Returns:
    
    true when squared.
  - 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