mulan.evaluation.measure
Class MeanAverageInterpolatedPrecision

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

All Implemented Interfaces:

Serializable, MacroAverageMeasure, Measure

Direct Known Subclasses:

GeometricMeanAverageInterpolatedPrecision

public class MeanAverageInterpolatedPrecision
extends LabelBasedAveragePrecision
implements MacroAverageMeasure

Implementation of MAiP (Mean Average Interpolated Precision)

Version:

2012.07.28

Author:

Fragkiskos Chatziasimidis, John Panagos, 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

MeanAverageInterpolatedPrecision(int numOfLabels, int numRecallLevels)
Constructor

Method Summary

double	getIdealValue() Gets an 'ideal' value of a measure.
String	getName() Gets the name of a measure.
double	getValue() Gets the value of a measure.
double	getValue(int labelIndex) Returns the average interpolated 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

MeanAverageInterpolatedPrecision

public MeanAverageInterpolatedPrecision(int numOfLabels,
                                        int numRecallLevels)

Constructor

Parameters:

numOfLabels - the number of labels

numRecallLevels - the number of standard recall levels uniformly distributed in [0,1]

Method Detail

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.

getValue

public double getValue()

Description copied from interface: Measure

Gets the value of a measure. The measure is incrementally cumulated for learner's prediction by each Measure.update(MultiLabelOutput, boolean[]) call. The value returned by the method, returns sum of all update calls divided by the number of calls (average of all measures for all predictions).

Specified by:

getValue in interface Measure

Returns:

the average measure value computed so far

getValue

public double getValue(int labelIndex)

Returns the average interpolated precision for a label

Specified by:

getValue in interface MacroAverageMeasure

Parameters:

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

Returns:

the average interpolated precision for the given label

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