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

Class RankingQualityHistogram<O,D extends NumberDistance<D,?>>

java.lang.Object

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

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

de.lmu.ifi.dbs.elki.algorithm.statistics.RankingQualityHistogram<O,D>

Type Parameters:

O - Object type

D - Distance type

All Implemented Interfaces:

Algorithm, Parameterizable

@Title(value="Ranking Quality Histogram")
@Description(value="Evaluates the effectiveness of a distance function via the obtained rankings.")
public class RankingQualityHistogram<O,D extends NumberDistance<D,?>>
extends AbstractDistanceBasedAlgorithm<O,D,CollectionResult<DoubleVector>>

Evaluate a distance function with respect to kNN queries. For each point, the neighbors are sorted by distance, then the ROC AUC is computed. A score of 1 means that the distance function provides a perfect ordering of relevant neighbors first, then irrelevant neighbors. A value of 0.5 can be obtained by random sorting. A value of 0 means the distance function is inverted, i.e. a similarity. TODO: Add sampling

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	RankingQualityHistogram.Parameterizer<O,D extends NumberDistance<D,?>> Parameterization class.

Field Summary

Fields

Modifier and Type	Field and Description
static OptionID	HISTOGRAM_BINS_ID Option to configure the number of bins to use.
private static Logging	LOG The logger for this class.
(package private) int	numbins Number of bins to use.

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

DISTANCE_FUNCTION_ID

Constructor Summary

Constructors

Constructor and Description
RankingQualityHistogram(DistanceFunction<? super O,D> distanceFunction, int numbins) 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, Relation<O> relation) Process a database

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

getDistanceFunction

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

makeParameterDistanceFunction, run

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.

HISTOGRAM_BINS_ID

public static final OptionID HISTOGRAM_BINS_ID

Option to configure the number of bins to use.

numbins

int numbins

Number of bins to use.

Constructor Detail

RankingQualityHistogram

public RankingQualityHistogram(DistanceFunction<? super O,D> distanceFunction,
                       int numbins)

Constructor.

Parameters:

distanceFunction - Distance function to evaluate

numbins - Number of bins

Method Detail

run

public HistogramResult<DoubleVector> run(Database database,
                                Relation<O> relation)

Process a database

Parameters:

database - Database to process

relation - Relation to process

Returns:

Histogram of ranking qualities

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