de.lmu.ifi.dbs.elki.algorithm.statistics

Class AveragePrecisionAtK<O>

java.lang.Object

de.lmu.ifi.dbs.elki.algorithm.AbstractAlgorithm<R>

de.lmu.ifi.dbs.elki.algorithm.AbstractDistanceBasedAlgorithm<O,CollectionResult<DoubleVector>>

de.lmu.ifi.dbs.elki.algorithm.statistics.AveragePrecisionAtK<O>

Type Parameters:

O - Object type

All Implemented Interfaces:

Algorithm, DistanceBasedAlgorithm<O>

public class AveragePrecisionAtK<O>
extends AbstractDistanceBasedAlgorithm<O,CollectionResult<DoubleVector>>

Evaluate a distance functions performance by computing the average precision at k, when ranking the objects by distance.

Since:

0.5.0

Author:

Erich Schubert

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	AveragePrecisionAtK.Parameterizer<O> Parameterization class.

Field Summary

Fields

Modifier and Type	Field and Description
private boolean	includeSelf Include query object in evaluation.
private int	k The parameter k - the number of neighbors to retrieve.
private static Logging	LOG The logger for this class.
private RandomFactory	random Random sampling seed.
private double	sampling Relative number of object to use in sampling.

Fields inherited from class de.lmu.ifi.dbs.elki.algorithm.AbstractAlgorithm

ALGORITHM_ID

Fields inherited from interface de.lmu.ifi.dbs.elki.algorithm.DistanceBasedAlgorithm

DISTANCE_FUNCTION_ID

Constructor Summary

Constructors

Constructor and Description
AveragePrecisionAtK(DistanceFunction<? super O> distanceFunction, int k, double sampling, RandomFactory random, boolean includeSelf) Constructor.

Method Summary

Modifier and Type	Method and Description
TypeInformation[]	getInputTypeRestriction() Get the input type restriction used for negotiating the data query.
protected Logging	getLogger() Get the (STATIC) logger for this class.
protected static boolean	match(java.lang.Object ref, java.lang.Object test) Test whether two relation agree.
CollectionResult<double[]>	run(Database database, Relation<O> relation, Relation<?> lrelation) Run the algorithm

Methods inherited from class de.lmu.ifi.dbs.elki.algorithm.AbstractDistanceBasedAlgorithm

getDistanceFunction

Methods inherited from class de.lmu.ifi.dbs.elki.algorithm.AbstractAlgorithm

run

Methods inherited from class java.lang.Object

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

Methods inherited from interface de.lmu.ifi.dbs.elki.algorithm.Algorithm

run

Field Detail

LOG

private static final Logging LOG

The logger for this class.

k

private int k

The parameter k - the number of neighbors to retrieve.

sampling

private double sampling

Relative number of object to use in sampling.

random

private RandomFactory random

Random sampling seed.

includeSelf

private boolean includeSelf

Include query object in evaluation.

Constructor Detail

AveragePrecisionAtK

public AveragePrecisionAtK(DistanceFunction<? super O> distanceFunction,
                           int k,
                           double sampling,
                           RandomFactory random,
                           boolean includeSelf)

Constructor.

Parameters:

distanceFunction - Distance function

k - K parameter

sampling - Sampling rate

random - Random sampling generator

includeSelf - Include query object in evaluation

Method Detail

run

public CollectionResult<double[]> run(Database database,
                                      Relation<O> relation,
                                      Relation<?> lrelation)

Run the algorithm

Parameters:

database - Database to run on (for kNN queries)

relation - Relation for distance computations

lrelation - Relation for class label comparison

Returns:

Vectors containing mean and standard deviation.

match

protected static boolean match(java.lang.Object ref,
                               java.lang.Object test)

Test whether two relation agree.

Parameters:

ref - Reference object

test - Test object

Returns:

true if the objects match

getInputTypeRestriction

public TypeInformation[] getInputTypeRestriction()

Description copied from class: AbstractAlgorithm

Get the input type restriction used for negotiating the data query.

Specified by:

getInputTypeRestriction in interface Algorithm

Specified by:

getInputTypeRestriction in class AbstractAlgorithm<CollectionResult<DoubleVector>>

Returns:

Type restriction

getLogger

protected Logging getLogger()

Description copied from class: AbstractAlgorithm

Get the (STATIC) logger for this class.

Specified by:

getLogger in class AbstractAlgorithm<CollectionResult<DoubleVector>>

Returns:

the static logger