mulan.evaluation.measure
Class MeanAveragePrecision

java.lang.Object
  mulan.evaluation.measure.MeasureBase
      mulan.evaluation.measure.ConfidenceMeasureBase
          mulan.evaluation.measure.LabelBasedAveragePrecision
              mulan.evaluation.measure.MeanAveragePrecision

All Implemented Interfaces:

Serializable, MacroAverageMeasure, Measure

Direct Known Subclasses:

GeometricMeanAveragePrecision

public class MeanAveragePrecision
extends LabelBasedAveragePrecision
implements MacroAverageMeasure

Implementation of MAP (Mean Average Precision)

Version:

2010.12.10

Author:

Eleftherios Spyromitros-Xioufis

See Also:

Serialized Form

Nested Class Summary

Nested classes/interfaces inherited from class mulan.evaluation.measure.LabelBasedAveragePrecision

LabelBasedAveragePrecision.ConfidenceActual

Field Summary

Fields inherited from class mulan.evaluation.measure.LabelBasedAveragePrecision

confact, numOfLabels

Constructor Summary

MeanAveragePrecision(int numOfLabels)
Creates a new instance of this class

Method Summary

double	getIdealValue() Gets an 'ideal' value of a measure.
String	getName() Gets the name of a measure.
double	getValue() Calculates map using multiple calls to getValue(int).
double	getValue(int labelIndex) Returns the average precision for a label.

Methods inherited from class mulan.evaluation.measure.LabelBasedAveragePrecision

reset, updateConfidence

Methods inherited from class mulan.evaluation.measure.ConfidenceMeasureBase

updateInternal

Methods inherited from class mulan.evaluation.measure.MeasureBase

makeCopy, toString, update

Methods inherited from class java.lang.Object

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

Constructor Detail

MeanAveragePrecision

public MeanAveragePrecision(int numOfLabels)

Creates a new instance of this class

Parameters:

numOfLabels - the number of labels

Method Detail

getValue

public double getValue()

Calculates map using multiple calls to getValue(int). If a label has 0 relevant examples, then it is omitted from the average.

Specified by:

getValue in interface Measure

Returns:

the average measure value computed so far

getValue

public double getValue(int labelIndex)

Returns the average precision for a label. If there are no relevant examples for a given label, Double.NaN is returned.

Specified by:

getValue in interface MacroAverageMeasure

Parameters:

labelIndex - the index of a label (starting from 0)

Returns:

the average precision for the given label

getName

public String getName()

Description copied from interface: Measure

Gets the name of a measure.

Specified by:

getName in interface Measure

Returns:

the name of a measure.

getIdealValue

public double getIdealValue()

Description copied from interface: Measure

Gets an 'ideal' value of a measure. The 'ideal' means, that the value represents the best achievable performance of a learner for an prediction of a multi-label task and associated true labels.

Specified by:

getIdealValue in interface Measure

Returns:

the ideal value