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

Class AveragePrecisionAtK<V,D extends NumberDistance<D,?>>

java.lang.Object

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

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

de.lmu.ifi.dbs.elki.algorithm.statistics.AveragePrecisionAtK<V,D>

Type Parameters:

V - Vector type

D - Distance type

All Implemented Interfaces:

Algorithm, InspectionUtilFrequentlyScanned, Parameterizable

public class AveragePrecisionAtK<V,D extends NumberDistance<D,?>>
extends AbstractDistanceBasedAlgorithm<V,D,CollectionResult<DoubleVector>>

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

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	AveragePrecisionAtK.Parameterizer<V extends NumberVector<?>,D extends NumberDistance<D,?>> Parameterization class.

Field Summary

Fields

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

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

DISTANCE_FUNCTION_ID

Constructor Summary

Constructors

Constructor and Description
AveragePrecisionAtK(DistanceFunction<? super V,D> distanceFunction, int k, double sampling, Long seed) Constructor.

Method Summary

Methods

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.
HistogramResult<DoubleVector>	run(Database database) Runs 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

makeParameterDistanceFunction

Methods inherited from class java.lang.Object

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

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.

seed

private Long seed

Random sampling seed.

Constructor Detail

AveragePrecisionAtK

public AveragePrecisionAtK(DistanceFunction<? super V,D> distanceFunction,
                   int k,
                   double sampling,
                   Long seed)

Constructor.

Parameters:

distanceFunction - Distance function

k - K parameter

sampling - Sampling rate

seed - Random sampling seed (may be null)

Method Detail

run

public HistogramResult<DoubleVector> run(Database database)

Description copied from interface: Algorithm

Runs the algorithm.

Specified by:

run in interface Algorithm

Overrides:

run in class AbstractAlgorithm<CollectionResult<DoubleVector>>

Parameters:

database - the database to run the algorithm on

Returns:

the Result computed by this algorithm

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