de.aitools.dm.clusterlabeling.validation.external.measure
Class MeanAveragePrecision

java.lang.Object
  de.aitools.dm.clusterlabeling.validation.external.PreferencedMeasure
      de.aitools.dm.clusterlabeling.validation.external.measure.MeanAveragePrecision

All Implemented Interfaces:

ExternalMeasure

public class MeanAveragePrecision
extends PreferencedMeasure

PrecisionAtN: Number of labels in the top N results that match the reference-label divided by N. MAP: Sum of PrecisionAtN for all N where label N matches, divided by number of matching lables.

Version:

$Id: MeanAveragePrecision.java,v 1.1 2011/02/18 16:08:22 hoppe Exp $

Author:

johannes.kiesel(/\t)uni-weimar.de

Constructor Summary

MeanAveragePrecision(MeasurePreferences preferences)

Method Summary

double	eval() This will evaluate depending on the concrete implementation.
double	evalAt(int n) This will evaluate depending on the concrete implementation.

Methods inherited from class de.aitools.dm.clusterlabeling.validation.external.PreferencedMeasure

evalClusterLabels, evalReferenceLabel, getClusterLabels, getReferenceLabel, setClusterLabels, setReferenceLabel

Methods inherited from class java.lang.Object

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

Constructor Detail

MeanAveragePrecision

public MeanAveragePrecision(MeasurePreferences preferences)

Method Detail

eval

public double eval()

Description copied from interface: ExternalMeasure

This will evaluate depending on the concrete implementation.
Attention: The return-value may vary significantly in its meaning depending on the implementation. Higher values should suggest closer pairs.

evalAt

public double evalAt(int n)

Description copied from interface: ExternalMeasure

This will evaluate depending on the concrete implementation.
Attention: The return-value may vary significantly in its meaning depending on the implementation. Higher values should suggest closer pairs.