mulan.evaluation.loss
Class OneMinusAveragePrecision

java.lang.Object
  mulan.evaluation.loss.RankingLossFunctionBase
      mulan.evaluation.loss.OneMinusAveragePrecision

All Implemented Interfaces:

Serializable, MultiLabelLossFunction, RankingLossFunction

public class OneMinusAveragePrecision
extends RankingLossFunctionBase

Implementation of the average precision as loss function.

Version:

2010.12.14

Author:

Grigorios Tsoumakas

See Also:

Serialized Form

Constructor Summary

OneMinusAveragePrecision()

Method Summary

double	computeLoss(int[] ranking, boolean[] trueLabels) Computes the ranking loss function
String	getName() Returns the name of the loss function

Methods inherited from class mulan.evaluation.loss.RankingLossFunctionBase

computeLoss

Methods inherited from class java.lang.Object

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

Constructor Detail

OneMinusAveragePrecision

public OneMinusAveragePrecision()

Method Detail

getName

public String getName()

Description copied from interface: MultiLabelLossFunction

Returns the name of the loss function

Returns:

the name of the loss function

computeLoss

public double computeLoss(int[] ranking,
                          boolean[] trueLabels)

Description copied from interface: RankingLossFunction

Computes the ranking loss function

Specified by:

computeLoss in interface RankingLossFunction

Specified by:

computeLoss in class RankingLossFunctionBase

Parameters:

ranking - the ranking of the learner for an example

trueLabels - the ground truth of the example

Returns:

the value of the loss function