Uses of Class
ciir.umass.edu.learning.RankList

Packages that use RankList

Package	Description
ciir.umass.edu.eval
ciir.umass.edu.features
ciir.umass.edu.learning
ciir.umass.edu.learning.boosting
ciir.umass.edu.learning.neuralnet
ciir.umass.edu.learning.tree
ciir.umass.edu.metric

Uses of RankList in ciir.umass.edu.eval

Methods in ciir.umass.edu.eval that return types with arguments of type RankList

Modifier and Type	Method	Description
java.util.List<RankList>	Evaluator.readInput(java.lang.String inputFile)

Method parameters in ciir.umass.edu.eval with type arguments of type RankList

Modifier and Type	Method	Description
double	Evaluator.evaluate(Ranker ranker, java.util.List<RankList> rl)
void	Evaluator.normalize(java.util.List<RankList> samples)
void	Evaluator.normalize(java.util.List<RankList> samples, int[] fids)
void	Evaluator.normalizeAll(java.util.List<java.util.List<RankList>> samples, int[] fids)

Uses of RankList in ciir.umass.edu.features

Methods in ciir.umass.edu.features that return types with arguments of type RankList

Modifier and Type	Method	Description
static java.util.List<RankList>	FeatureManager.readInput(java.lang.String inputFile)	Read a set of rankings from a single file.
static java.util.List<RankList>	FeatureManager.readInput(java.lang.String inputFile, boolean mustHaveRelDoc, boolean useSparseRepresentation)	Read a set of rankings from a single file.
static java.util.List<RankList>	FeatureManager.readInput(java.util.List<java.lang.String> inputFiles)	Read sets of rankings from multiple files.

Methods in ciir.umass.edu.features with parameters of type RankList

Modifier and Type	Method	Description
void	LinearNormalizer.normalize(RankList rl)
void	LinearNormalizer.normalize(RankList rl, int[] fids)
void	Normalizer.normalize(RankList rl)
void	Normalizer.normalize(RankList rl, int[] fids)
void	SumNormalizor.normalize(RankList rl)
void	SumNormalizor.normalize(RankList rl, int[] fids)
void	ZScoreNormalizor.normalize(RankList rl)
void	ZScoreNormalizor.normalize(RankList rl, int[] fids)
int	Normalizer.numFeatures(RankList rl)

Method parameters in ciir.umass.edu.features with type arguments of type RankList

Modifier and Type	Method	Description
static int[]	FeatureManager.getFeatureFromSampleVector(java.util.List<RankList> samples)	Obtain all features present in a sample set.
void	Normalizer.normalize(java.util.List<RankList> samples)
void	Normalizer.normalize(java.util.List<RankList> samples, int[] fids)
static void	FeatureManager.prepareCV(java.util.List<RankList> samples, int nFold, float tvs, java.util.List<java.util.List<RankList>> trainingData, java.util.List<java.util.List<RankList>> validationData, java.util.List<java.util.List<RankList>> testData)	Split the input sample set into k chunks (folds) of roughly equal size and create train/test data for each fold.
static void	FeatureManager.prepareCV(java.util.List<RankList> samples, int nFold, java.util.List<java.util.List<RankList>> trainingData, java.util.List<java.util.List<RankList>> testData)	Split the input sample set into k chunks (folds) of roughly equal size and create train/test data for each fold.
static void	FeatureManager.prepareSplit(java.util.List<RankList> samples, double percentTrain, java.util.List<RankList> trainingData, java.util.List<RankList> testData)	Split the input sample set into 2 chunks: one for training and one for either validation or testing
static void	FeatureManager.printQueriesForSplit(java.lang.String name, java.util.List<java.util.List<RankList>> split)
static void	FeatureManager.save(java.util.List<RankList> samples, java.lang.String outputFile)	Save a sample set to file

Uses of RankList in ciir.umass.edu.learning

Fields in ciir.umass.edu.learning with type parameters of type RankList

Modifier and Type	Field	Description
protected java.util.List<RankList>	Sampler.remains
protected java.util.List<RankList>	Ranker.samples
protected java.util.List<RankList>	Sampler.samples
protected java.util.List<RankList>	Ranker.validationSamples

Methods in ciir.umass.edu.learning that return RankList

Modifier and Type	Method	Description
RankList	RankList.getCorrectRanking()
RankList	RankList.getRanking(short fid)
RankList	CoorAscent.rank(RankList rl)
RankList	Ranker.rank(RankList rl)

Methods in ciir.umass.edu.learning that return types with arguments of type RankList

Modifier and Type	Method	Description
java.util.List<RankList>	Sampler.doSampling(java.util.List<RankList> samplingPool, float samplingRate, boolean withReplacement)
java.util.List<RankList>	Sampler.getRemains()
java.util.List<RankList>	Sampler.getSamples()
java.util.List<RankList>	Ranker.rank(java.util.List<RankList> l)

Methods in ciir.umass.edu.learning with parameters of type RankList

Modifier and Type	Method	Description
RankList	CoorAscent.rank(RankList rl)
RankList	Ranker.rank(RankList rl)

Method parameters in ciir.umass.edu.learning with type arguments of type RankList

Modifier and Type	Method	Description
Ranker	RankerFactory.createRanker(RANKER_TYPE type, java.util.List<RankList> samples, int[] features, MetricScorer scorer)
Ranker	RankerFactory.createRanker(java.lang.String className, java.util.List<RankList> samples, int[] features, MetricScorer scorer)
java.util.List<RankList>	Sampler.doSampling(java.util.List<RankList> samplingPool, float samplingRate, boolean withReplacement)
java.util.List<RankList>	Ranker.rank(java.util.List<RankList> l)
void	Ranker.setTrainingSet(java.util.List<RankList> samples)
void	Ranker.setValidationSet(java.util.List<RankList> samples)
Ranker	RankerTrainer.train(RANKER_TYPE type, java.util.List<RankList> train, int[] features, MetricScorer scorer)
Ranker	RankerTrainer.train(RANKER_TYPE type, java.util.List<RankList> train, java.util.List<RankList> validation, int[] features, MetricScorer scorer)

Constructors in ciir.umass.edu.learning with parameters of type RankList

Constructor	Description
RankList(RankList rl)
RankList(RankList rl, int[] idx)
RankList(RankList rl, int[] idx, int offset)

Constructor parameters in ciir.umass.edu.learning with type arguments of type RankList

Constructor	Description
CoorAscent(java.util.List<RankList> samples, int[] features, MetricScorer scorer)
LinearRegRank(java.util.List<RankList> samples, int[] features, MetricScorer scorer)
Ranker(java.util.List<RankList> samples, int[] features, MetricScorer scorer)

Uses of RankList in ciir.umass.edu.learning.boosting

Methods in ciir.umass.edu.learning.boosting that return RankList

Modifier and Type	Method	Description
RankList	WeakRanker.rank(RankList l)

Methods in ciir.umass.edu.learning.boosting that return types with arguments of type RankList

Modifier and Type	Method	Description
java.util.List<RankList>	WeakRanker.rank(java.util.List<RankList> l)

Methods in ciir.umass.edu.learning.boosting with parameters of type RankList

Modifier and Type	Method	Description
RankList	WeakRanker.rank(RankList l)

Method parameters in ciir.umass.edu.learning.boosting with type arguments of type RankList

Modifier and Type	Method	Description
java.util.List<RankList>	WeakRanker.rank(java.util.List<RankList> l)

Constructor parameters in ciir.umass.edu.learning.boosting with type arguments of type RankList

Constructor	Description
AdaRank(java.util.List<RankList> samples, int[] features, MetricScorer scorer)
RankBoost(java.util.List<RankList> samples, int[] features, MetricScorer scorer)

Uses of RankList in ciir.umass.edu.learning.neuralnet

Methods in ciir.umass.edu.learning.neuralnet that return RankList

Modifier and Type	Method	Description
protected RankList	LambdaRank.internalReorder(RankList rl)
protected RankList	RankNet.internalReorder(RankList rl)

Methods in ciir.umass.edu.learning.neuralnet with parameters of type RankList

Modifier and Type	Method	Description
protected int[][]	LambdaRank.batchFeedForward(RankList rl)
protected int[][]	RankNet.batchFeedForward(RankList rl)
protected float[][]	LambdaRank.computePairWeight(int[][] pairMap, RankList rl)
protected float[][]	RankNet.computePairWeight(int[][] pairMap, RankList rl)
protected float[]	ListNet.feedForward(RankList rl)
protected RankList	LambdaRank.internalReorder(RankList rl)
protected RankList	RankNet.internalReorder(RankList rl)

Constructor parameters in ciir.umass.edu.learning.neuralnet with type arguments of type RankList

Constructor	Description
LambdaRank(java.util.List<RankList> samples, int[] features, MetricScorer scorer)
ListNet(java.util.List<RankList> samples, int[] features, MetricScorer scorer)
RankNet(java.util.List<RankList> samples, int[] features, MetricScorer scorer)

Uses of RankList in ciir.umass.edu.learning.tree

Methods in ciir.umass.edu.learning.tree that return RankList

Modifier and Type	Method	Description
protected RankList	LambdaMART.rank(int rankListIndex, int current)	This function is equivalent to the inherited function rank(...), but it uses the cached model's outputs instead of computing them from scratch.

Constructor parameters in ciir.umass.edu.learning.tree with type arguments of type RankList

Constructor	Description
LambdaMART(java.util.List<RankList> samples, int[] features, MetricScorer scorer)
MART(java.util.List<RankList> samples, int[] features, MetricScorer scorer)
RFRanker(java.util.List<RankList> samples, int[] features, MetricScorer scorer)

Uses of RankList in ciir.umass.edu.metric

Methods in ciir.umass.edu.metric with parameters of type RankList

Modifier and Type	Method	Description
protected int[]	MetricScorer.getRelevanceLabels(RankList rl)
int	BestAtKScorer.maxToK(RankList rl, int k)	Return the position of the best object (e.g.
double	APScorer.score(RankList rl)	Compute Average Precision (AP) of the list.
double	BestAtKScorer.score(RankList rl)
double	DCGScorer.score(RankList rl)	Compute DCG at k.
double	ERRScorer.score(RankList rl)	Compute ERR at k.
abstract double	MetricScorer.score(RankList rl)
double	NDCGScorer.score(RankList rl)	Compute NDCG at k.
double	PrecisionScorer.score(RankList rl)
double	ReciprocalRankScorer.score(RankList rl)
double[][]	APScorer.swapChange(RankList rl)
double[][]	BestAtKScorer.swapChange(RankList rl)
double[][]	DCGScorer.swapChange(RankList rl)
double[][]	ERRScorer.swapChange(RankList rl)
abstract double[][]	MetricScorer.swapChange(RankList rl)
double[][]	NDCGScorer.swapChange(RankList rl)
double[][]	PrecisionScorer.swapChange(RankList rl)
double[][]	ReciprocalRankScorer.swapChange(RankList rl)

Method parameters in ciir.umass.edu.metric with type arguments of type RankList

Modifier and Type	Method	Description
double	MetricScorer.score(java.util.List<RankList> rl)