edu.cmu.minorthird.classify.ranking
Class RankingBoosted

java.lang.Object
  edu.cmu.minorthird.classify.BatchClassifierLearner
      edu.cmu.minorthird.classify.BatchBinaryClassifierLearner
          edu.cmu.minorthird.classify.ranking.BatchRankingLearner
              edu.cmu.minorthird.classify.ranking.RankingBoosted

All Implemented Interfaces:

BinaryClassifierLearner, ClassifierLearner, java.lang.Cloneable

public class RankingBoosted
extends BatchRankingLearner

A boosted version for ranking. An implementation of - "Michael Collins and Terry Koo, Discriminative Reranking for Natural Language Parsing. Computational Linguistics, March 2005", see page 45. Requirements of this class: - Considers only binary features - Requires a particular cont. feature named "walkerScore", that contains the original log-probability for an example To do: - Handle multiple positive answers. - Automatically discretize real-value features into binary. - It is possible to incorporate example 'importance' weights, according to some 'goodness' evaluation measure. See Collins'.

Author:

Einat Minkov

Field Summary

Fields inherited from class edu.cmu.minorthird.classify.BatchClassifierLearner

classifier, dataset

Constructor Summary

RankingBoosted()

RankingBoosted(int numEpochs, int exampleSize)

Method Summary

Classifier	batchTrain(Dataset data) subclasses should use this method to implement a batch supervised learning algorithm.
double	initialExpLoss(double w0, Example[][] rankedExamples)

Methods inherited from class edu.cmu.minorthird.classify.ranking.BatchRankingLearner

listsWithOneExampleEach, sortByScore, splitIntoRankings

Methods inherited from class edu.cmu.minorthird.classify.BatchBinaryClassifierLearner

batchTrainBinary, getBinaryClassifier, getSchema, setSchema

Methods inherited from class edu.cmu.minorthird.classify.BatchClassifierLearner

addExample, completeTraining, copy, getClassifier, hasNextQuery, nextQuery, reset, setInstancePool

Methods inherited from class java.lang.Object

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

Methods inherited from interface edu.cmu.minorthird.classify.ClassifierLearner

addExample, completeTraining, copy, getClassifier, hasNextQuery, nextQuery, reset, setInstancePool

Constructor Detail

RankingBoosted

public RankingBoosted()

RankingBoosted

public RankingBoosted(int numEpochs,
                      int exampleSize)

Method Detail

batchTrain

public Classifier batchTrain(Dataset data)

Description copied from class: BatchClassifierLearner

subclasses should use this method to implement a batch supervised learning algorithm.

Specified by:

batchTrain in class BatchClassifierLearner

initialExpLoss

public double initialExpLoss(double w0,
                             Example[][] rankedExamples)