jsat.linear.distancemetrics

Class PearsonDistance

java.lang.Object

jsat.linear.distancemetrics.PearsonDistance

All Implemented Interfaces:

Serializable, Cloneable, DistanceMetric

public class PearsonDistance
extends Object
implements DistanceMetric

A valid distance metric formed from the Pearson Correlation between two vectors. The distance in the range of [0, 1].

Author:

Edward Raff

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
PearsonDistance() Creates a new standard Pearson Distance that does not ignore zero values and anti-correlated values are considered far away.
PearsonDistance(boolean bothNonZero, boolean absoluteDistance) Creates a new Pearson Distance object

Method Summary

Modifier and Type	Method and Description
PearsonDistance	clone()
static double	correlation(Vec a, Vec b, boolean bothNonZero) Computes the Pearson correlation between two vectors.
double	dist(int a, int b, List<? extends Vec> vecs, List<Double> cache) Computes the distance between 2 vectors in the original list of vectors.
double	dist(int a, Vec b, List<? extends Vec> vecs, List<Double> cache) Computes the distance between one vector in the original list of vectors with that of another vector not from the original list.
double	dist(int a, Vec b, List<Double> qi, List<? extends Vec> vecs, List<Double> cache) Computes the distance between one vector in the original list of vectors with that of another vector not from the original list, but had information generated by DistanceMetric.getQueryInfo(jsat.linear.Vec).
double	dist(Vec a, Vec b) Computes the distance between 2 vectors.
List<Double>	getAccelerationCache(List<? extends Vec> vecs) Returns a cache of double values associated with the given list of vectors in the given order.
List<Double>	getAccelerationCache(List<? extends Vec> vecs, ExecutorService threadpool) Returns a cache of double values associated with the given list of vectors in the given order.
List<Double>	getQueryInfo(Vec q) Pre computes query information that would have be generated if the query was a member of the original list of vectors when calling DistanceMetric.getAccelerationCache(java.util.List) .
boolean	isIndiscemible() Returns true if this distance metric obeys the rule that, for any x and y ∈ S d(x, y) = 0 if and only if x = y
boolean	isSubadditive() Returns true if this distance metric obeys the rule that, for any x, y, and z ∈ S d(x, z) ≤ d(x, y) + d(y, z)
boolean	isSymmetric() Returns true if this distance metric obeys the rule that, for any x, y, and z ∈ S d(x, y) = d(y, x)
double	metricBound() All metrics must return values greater than or equal to 0.
boolean	supportsAcceleration() Indicates if this distance metric supports building an acceleration cache using the DistanceMetric.getAccelerationCache(java.util.List) and associated distance methods.

Methods inherited from class java.lang.Object

equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface jsat.linear.distancemetrics.DistanceMetric

toString

Constructor Detail

PearsonDistance

public PearsonDistance()

Creates a new standard Pearson Distance that does not ignore zero values and anti-correlated values are considered far away.

PearsonDistance

public PearsonDistance(boolean bothNonZero,
                       boolean absoluteDistance)

Creates a new Pearson Distance object

Parameters:

bothNonZero - true if non zero values should be treated as "missing" or "no vote", and will not contribute. But this will not change the mean value used. false produces the standard Pearson value.

absoluteDistance - true to use the absolute correlation, meaning correlated and anti-correlated values will have the same distance.

Method Detail

dist

public double dist(Vec a,
                   Vec b)

Description copied from interface: DistanceMetric

Computes the distance between 2 vectors. The smaller the value, the closer, and there for, more similar, the vectors are. 0 indicates the vectors are the same.

Specified by:

dist in interface DistanceMetric

Parameters:

a - the first vector

b - the second vector

Returns:

the distance between them

isSymmetric

public boolean isSymmetric()

Description copied from interface: DistanceMetric

Returns true if this distance metric obeys the rule that, for any x, y, and z ∈ S
d(x, y) = d(y, x)

Specified by:

isSymmetric in interface DistanceMetric

Returns:

true if this distance metric is symmetric, false if it is not

isSubadditive

public boolean isSubadditive()

Description copied from interface: DistanceMetric

Returns true if this distance metric obeys the rule that, for any x, y, and z ∈ S
d(x, z) ≤ d(x, y) + d(y, z)

Specified by:

isSubadditive in interface DistanceMetric

Returns:

true if this distance metric supports the triangle inequality, false if it does not.

isIndiscemible

public boolean isIndiscemible()

Description copied from interface: DistanceMetric

Returns true if this distance metric obeys the rule that, for any x and y ∈ S
d(x, y) = 0 if and only if x = y

Specified by:

isIndiscemible in interface DistanceMetric

Returns:

true if this distance metric is indicemible, false otherwise.

metricBound

public double metricBound()

Description copied from interface: DistanceMetric

All metrics must return values greater than or equal to 0. The upper bound on the value returned is different for different metrics. This method returns the theoretical maximal value that could be returned by this distance metric. That means Double.POSITIVE_INFINITY is a valid return value.

Specified by:

metricBound in interface DistanceMetric

Returns:

the maximal distance for any two points in that could exist by this distance metric.

clone

public PearsonDistance clone()

Specified by:

clone in interface DistanceMetric

Overrides:

clone in class Object

correlation

public static double correlation(Vec a,
                                 Vec b,
                                 boolean bothNonZero)

Computes the Pearson correlation between two vectors. If one of the vectors is all zeros, the result is undefined. In cases where both are zero vectors, 1 will be returned to indicate they are the same. In cases where one of the numerator coefficients is zero, its value will be bumped up to an epsilon to provide a near result.

In cases where bothNonZero is true, and the vectors have no overlapping non zero values, 0 will be returned.

Parameters:

a - the first vector

b - the second vector

bothNonZero - false is the normal Pearson correlation. true will make the computation ignore all indexes where one of the values is zero, the mean will be from all non zero values in each vector.

Returns:

the Pearson correlation in [-1, 1]

supportsAcceleration

public boolean supportsAcceleration()

Description copied from interface: DistanceMetric

Indicates if this distance metric supports building an acceleration cache using the DistanceMetric.getAccelerationCache(java.util.List) and associated distance methods. By default this method will return false. If true, then a cache can be obtained from this distance metric and used in conjunction with DistanceMetric.dist(int, jsat.linear.Vec, java.util.List, java.util.List) and DistanceMetric.dist(int, int, java.util.List, java.util.List) to perform distance computations.

Specified by:

supportsAcceleration in interface DistanceMetric

Returns:

true if cache acceleration is supported for this metric, false otherwise.

getAccelerationCache

public List<Double> getAccelerationCache(List<? extends Vec> vecs)

Description copied from interface: DistanceMetric

Returns a cache of double values associated with the given list of vectors in the given order. This can be used by the distance metric to increase runtime at the cost of memory. This is an optional method.
If this metric does not support acceleration, null will be returned.

Specified by:

getAccelerationCache in interface DistanceMetric

Parameters:

vecs - the list of vectors to build an acceleration cache for

Returns:

the list of double for the cache

dist

public double dist(int a,
                   int b,
                   List<? extends Vec> vecs,
                   List<Double> cache)

Description copied from interface: DistanceMetric

Computes the distance between 2 vectors in the original list of vectors.
If the cache input is null, then DistanceMetric.dist(jsat.linear.Vec, jsat.linear.Vec) will be called directly.

Specified by:

dist in interface DistanceMetric

Parameters:

a - the index of the first vector

b - the index of the second vector

vecs - the list of vectors used to build the cache

cache - the cache associated with the given list of vectors

Returns:

the distance between the two vectors

dist

public double dist(int a,
                   Vec b,
                   List<? extends Vec> vecs,
                   List<Double> cache)

Description copied from interface: DistanceMetric

Computes the distance between one vector in the original list of vectors with that of another vector not from the original list.
If the cache input is null, then DistanceMetric.dist(jsat.linear.Vec, jsat.linear.Vec) will be called directly.

Specified by:

dist in interface DistanceMetric

Parameters:

a - the index of the vector in the cache

b - the other vector

vecs - the list of vectors used to build the cache

cache - the cache associated with the given list of vectors

Returns:

the distance between the two vectors

getQueryInfo

public List<Double> getQueryInfo(Vec q)

Description copied from interface: DistanceMetric

Pre computes query information that would have be generated if the query was a member of the original list of vectors when calling DistanceMetric.getAccelerationCache(java.util.List) . This can then be used if a large number of distance computations are going to be done against points in the original set for a point that is outside the original space.

If this metric does not support acceleration, null will be returned.

Specified by:

getQueryInfo in interface DistanceMetric

Parameters:

q - the query point to generate cache information for

Returns:

the cache information for the query point

getAccelerationCache

public List<Double> getAccelerationCache(List<? extends Vec> vecs,
                                         ExecutorService threadpool)

Description copied from interface: DistanceMetric

Returns a cache of double values associated with the given list of vectors in the given order. This can be used by the distance metric to increase runtime at the cost of memory. This is an optional method.
If this metric does not support acceleration, null will be returned.

Specified by:

getAccelerationCache in interface DistanceMetric

Parameters:

vecs - the list of vectors to build an acceleration cache for

threadpool - source of threads for parallel computation of result. This may be null, which means the singled threaded version may be used.

Returns:

the list of double for the cache

dist

public double dist(int a,
                   Vec b,
                   List<Double> qi,
                   List<? extends Vec> vecs,
                   List<Double> cache)

Description copied from interface: DistanceMetric

Computes the distance between one vector in the original list of vectors with that of another vector not from the original list, but had information generated by DistanceMetric.getQueryInfo(jsat.linear.Vec).
If the cache input is null, then DistanceMetric.dist(jsat.linear.Vec, jsat.linear.Vec) will be called directly.

Specified by:

dist in interface DistanceMetric

Parameters:

a - the index of the vector in the cache

b - the other vector

qi - the query information about b

vecs - the list of vectors used to build the cache

cache - the cache associated with the given list of vectors

Returns:

the distance between the two vectors