A B C D E F G H I K L M N O P Q R S T U V W Z
All Classes All Packages

A

AdaRank - Class in ciir.umass.edu.learning.boosting

AdaRank() - Constructor for class ciir.umass.edu.learning.boosting.AdaRank

AdaRank(List<RankList>, int[], MetricScorer) - Constructor for class ciir.umass.edu.learning.boosting.AdaRank

ADARANK - ciir.umass.edu.learning.RANKER_TYPE

add(RegressionTree, float) - Method in class ciir.umass.edu.learning.tree.Ensemble

addHiddenLayer(int) - Method in class ciir.umass.edu.learning.neuralnet.RankNet

addInput(DataPoint) - Method in class ciir.umass.edu.learning.neuralnet.RankNet

Auxiliary functions for pair-wise preference network learning.

addOutput(double) - Method in class ciir.umass.edu.learning.neuralnet.Neuron

afterExecute(Runnable, Throwable) - Method in class ciir.umass.edu.utilities.MyThreadPool

Analyzer - Class in ciir.umass.edu.eval

Analyzer() - Constructor for class ciir.umass.edu.eval.Analyzer

APScorer - Class in ciir.umass.edu.metric

APScorer() - Constructor for class ciir.umass.edu.metric.APScorer

await() - Method in class ciir.umass.edu.utilities.MyThreadPool

B

backPropagate(float[]) - Method in class ciir.umass.edu.learning.neuralnet.ListNet

backupSampleWeight - Variable in class ciir.umass.edu.learning.boosting.AdaRank

backupTrainScore - Variable in class ciir.umass.edu.learning.boosting.AdaRank

BasicStats - Class in ciir.umass.edu.stats

BasicStats() - Constructor for class ciir.umass.edu.stats.BasicStats

batchBackPropagate(int[][], float[][]) - Method in class ciir.umass.edu.learning.neuralnet.LambdaRank

batchBackPropagate(int[][], float[][]) - Method in class ciir.umass.edu.learning.neuralnet.RankNet

batchFeedForward(RankList) - Method in class ciir.umass.edu.learning.neuralnet.LambdaRank

batchFeedForward(RankList) - Method in class ciir.umass.edu.learning.neuralnet.RankNet

Best - ciir.umass.edu.metric.METRIC

BestAtKScorer - Class in ciir.umass.edu.metric

BestAtKScorer() - Constructor for class ciir.umass.edu.metric.BestAtKScorer

BestAtKScorer(int) - Constructor for class ciir.umass.edu.metric.BestAtKScorer

bestModelOnValidation - Variable in class ciir.umass.edu.learning.neuralnet.RankNet

bestModelOnValidation - Variable in class ciir.umass.edu.learning.tree.LambdaMART

bestModelRankers - Variable in class ciir.umass.edu.learning.boosting.AdaRank

bestModelRankers - Variable in class ciir.umass.edu.learning.boosting.RankBoost

bestModelWeights - Variable in class ciir.umass.edu.learning.boosting.AdaRank

bestModelWeights - Variable in class ciir.umass.edu.learning.boosting.RankBoost

bestScoreOnValidationData - Variable in class ciir.umass.edu.learning.Ranker

C

cached - Variable in class ciir.umass.edu.learning.DataPoint

ciir.umass.edu.eval - package ciir.umass.edu.eval

ciir.umass.edu.features - package ciir.umass.edu.features

ciir.umass.edu.learning - package ciir.umass.edu.learning

ciir.umass.edu.learning.boosting - package ciir.umass.edu.learning.boosting

ciir.umass.edu.learning.neuralnet - package ciir.umass.edu.learning.neuralnet

ciir.umass.edu.learning.tree - package ciir.umass.edu.learning.tree

ciir.umass.edu.metric - package ciir.umass.edu.metric

ciir.umass.edu.stats - package ciir.umass.edu.stats

ciir.umass.edu.utilities - package ciir.umass.edu.utilities

clearNeuronOutputs() - Method in class ciir.umass.edu.learning.neuralnet.RankNet

clearOutputs() - Method in class ciir.umass.edu.learning.neuralnet.Layer

clearOutputs() - Method in class ciir.umass.edu.learning.neuralnet.Neuron

clearSamples() - Method in class ciir.umass.edu.learning.tree.RegressionTree

Clear samples associated with each leaves (when they are no longer necessary) in order to save memory

clearSamples() - Method in class ciir.umass.edu.learning.tree.Split

clone() - Method in class ciir.umass.edu.utilities.WorkerThread

close() - Method in class ciir.umass.edu.utilities.TmpFile

combine(String, String) - Method in class ciir.umass.edu.learning.Combiner

Combiner - Class in ciir.umass.edu.learning

Combiner() - Constructor for class ciir.umass.edu.learning.Combiner

compare(String, String) - Method in class ciir.umass.edu.eval.Analyzer

Compare the performance of a set of systems to that of a baseline system

compare(HashMap<String, Double>, HashMap<String, Double>) - Method in class ciir.umass.edu.eval.Analyzer

Compare the performance of a target system to that of a baseline system

compare(HashMap<String, Double>, List<HashMap<String, Double>>) - Method in class ciir.umass.edu.eval.Analyzer

Compare the performance of a set of systems to that of a baseline system

compare(List<String>, String) - Method in class ciir.umass.edu.eval.Analyzer

Compare the performance of a set of systems to that of a baseline system

compute(double) - Method in class ciir.umass.edu.learning.neuralnet.HyperTangentFunction

compute(double) - Method in class ciir.umass.edu.learning.neuralnet.LogiFunction

compute(double) - Method in interface ciir.umass.edu.learning.neuralnet.TransferFunction

computeDelta(PropParameter) - Method in class ciir.umass.edu.learning.neuralnet.Layer

[Only for output layers] Compute delta for all neurons in the this (output) layer

computeDelta(PropParameter) - Method in class ciir.umass.edu.learning.neuralnet.ListNeuron

computeDelta(PropParameter) - Method in class ciir.umass.edu.learning.neuralnet.Neuron

Compute delta for neurons in the output layer.

computeDerivative(double) - Method in class ciir.umass.edu.learning.neuralnet.HyperTangentFunction

computeDerivative(double) - Method in class ciir.umass.edu.learning.neuralnet.LogiFunction

computeDerivative(double) - Method in interface ciir.umass.edu.learning.neuralnet.TransferFunction

computeModelScoreOnTraining() - Method in class ciir.umass.edu.learning.tree.LambdaMART

computeModelScoreOnTraining(int, int, int) - Method in class ciir.umass.edu.learning.tree.LambdaMART

computeModelScoreOnValidation() - Method in class ciir.umass.edu.learning.tree.LambdaMART

computeModelScoreOnValidation(int, int) - Method in class ciir.umass.edu.learning.tree.LambdaMART

computeOutput() - Method in class ciir.umass.edu.learning.neuralnet.Layer

computeOutput() - Method in class ciir.umass.edu.learning.neuralnet.Neuron

computeOutput(int) - Method in class ciir.umass.edu.learning.neuralnet.Layer

Have all neurons in this layer compute its output

computeOutput(int) - Method in class ciir.umass.edu.learning.neuralnet.Neuron

computePairWeight(int[][], RankList) - Method in class ciir.umass.edu.learning.neuralnet.LambdaRank

computePairWeight(int[][], RankList) - Method in class ciir.umass.edu.learning.neuralnet.RankNet

computePseudoResponses() - Method in class ciir.umass.edu.learning.tree.LambdaMART

computePseudoResponses() - Method in class ciir.umass.edu.learning.tree.MART

computePseudoResponses(int, int, int) - Method in class ciir.umass.edu.learning.tree.LambdaMART

connect(int, int, int, int) - Method in class ciir.umass.edu.learning.neuralnet.RankNet

construct(DataPoint[], double[], int[][], float[][], int, int) - Method in class ciir.umass.edu.learning.tree.FeatureHistogram

construct(DataPoint[], double[], int[][], int[], float[][]) - Method in class ciir.umass.edu.learning.tree.FeatureHistogram

construct(FeatureHistogram, int[], double[]) - Method in class ciir.umass.edu.learning.tree.FeatureHistogram

construct(FeatureHistogram, int[], double[], int, int) - Method in class ciir.umass.edu.learning.tree.FeatureHistogram

construct(FeatureHistogram, FeatureHistogram, boolean) - Method in class ciir.umass.edu.learning.tree.FeatureHistogram

construct(FeatureHistogram, FeatureHistogram, int, int) - Method in class ciir.umass.edu.learning.tree.FeatureHistogram

COOR_ASCENT - ciir.umass.edu.learning.RANKER_TYPE

CoorAscent - Class in ciir.umass.edu.learning

CoorAscent() - Constructor for class ciir.umass.edu.learning.CoorAscent

CoorAscent(List<RankList>, int[], MetricScorer) - Constructor for class ciir.umass.edu.learning.CoorAscent

copy() - Method in class ciir.umass.edu.metric.APScorer

copy() - Method in class ciir.umass.edu.metric.BestAtKScorer

copy() - Method in class ciir.umass.edu.metric.DCGScorer

copy() - Method in class ciir.umass.edu.metric.ERRScorer

copy() - Method in class ciir.umass.edu.metric.MetricScorer

copy() - Method in class ciir.umass.edu.metric.NDCGScorer

copy() - Method in class ciir.umass.edu.metric.PrecisionScorer

copy() - Method in class ciir.umass.edu.metric.ReciprocalRankScorer

copy(double[], double[]) - Method in class ciir.umass.edu.learning.Ranker

copyModel(CoorAscent) - Method in class ciir.umass.edu.learning.CoorAscent

count - Variable in class ciir.umass.edu.learning.tree.FeatureHistogram

create(Exception) - Static method in exception ciir.umass.edu.utilities.RankLibError

Don't rewrap RankLibErrors in RankLibErrors

create(String) - Static method in exception ciir.umass.edu.utilities.RankLibError

create(String, Exception) - Static method in exception ciir.umass.edu.utilities.RankLibError

Don't rewrap RankLibErrors in RankLibErrors

createNew() - Method in class ciir.umass.edu.learning.boosting.AdaRank

createNew() - Method in class ciir.umass.edu.learning.boosting.RankBoost

createNew() - Method in class ciir.umass.edu.learning.CoorAscent

createNew() - Method in class ciir.umass.edu.learning.LinearRegRank

createNew() - Method in class ciir.umass.edu.learning.neuralnet.LambdaRank

createNew() - Method in class ciir.umass.edu.learning.neuralnet.ListNet

createNew() - Method in class ciir.umass.edu.learning.neuralnet.RankNet

createNew() - Method in class ciir.umass.edu.learning.Ranker

createNew() - Method in class ciir.umass.edu.learning.tree.LambdaMART

createNew() - Method in class ciir.umass.edu.learning.tree.MART

createNew() - Method in class ciir.umass.edu.learning.tree.RFRanker

createRanker(RANKER_TYPE) - Method in class ciir.umass.edu.learning.RankerFactory

createRanker(RANKER_TYPE, List<RankList>, int[], MetricScorer) - Method in class ciir.umass.edu.learning.RankerFactory

createRanker(String) - Method in class ciir.umass.edu.learning.RankerFactory

createRanker(String, List<RankList>, int[], MetricScorer) - Method in class ciir.umass.edu.learning.RankerFactory

createScorer(METRIC) - Method in class ciir.umass.edu.metric.MetricScorerFactory

createScorer(METRIC, int) - Method in class ciir.umass.edu.metric.MetricScorerFactory

createScorer(String) - Method in class ciir.umass.edu.metric.MetricScorerFactory

crossEntropy(double, double, double) - Method in class ciir.umass.edu.learning.neuralnet.RankNet

current - Variable in class ciir.umass.edu.learning.neuralnet.PropParameter

current_feature - Variable in class ciir.umass.edu.learning.CoorAscent

D

d1 - Variable in class ciir.umass.edu.learning.neuralnet.ListNeuron

d2 - Variable in class ciir.umass.edu.learning.neuralnet.ListNeuron

DataPoint - Class in ciir.umass.edu.learning

DataPoint() - Constructor for class ciir.umass.edu.learning.DataPoint

Default constructor.

DataPoint(String) - Constructor for class ciir.umass.edu.learning.DataPoint

The input must have the form:

DCG - ciir.umass.edu.metric.METRIC

DCGScorer - Class in ciir.umass.edu.metric

DCGScorer() - Constructor for class ciir.umass.edu.metric.DCGScorer

DCGScorer(int) - Constructor for class ciir.umass.edu.metric.DCGScorer

delta_i - Variable in class ciir.umass.edu.learning.neuralnet.Neuron

deltas_j - Variable in class ciir.umass.edu.learning.neuralnet.Neuron

DenseDataPoint - Class in ciir.umass.edu.learning

DenseDataPoint(DenseDataPoint) - Constructor for class ciir.umass.edu.learning.DenseDataPoint

DenseDataPoint(String) - Constructor for class ciir.umass.edu.learning.DenseDataPoint

description - Variable in class ciir.umass.edu.learning.DataPoint

discount - Static variable in class ciir.umass.edu.metric.DCGScorer

discount(int) - Method in class ciir.umass.edu.metric.DCGScorer

distance(CoorAscent) - Method in class ciir.umass.edu.learning.CoorAscent

doSampling(List<RankList>, float, boolean) - Method in class ciir.umass.edu.learning.Sampler

dW - Variable in class ciir.umass.edu.learning.neuralnet.Synapse

E

end - Variable in class ciir.umass.edu.utilities.WorkerThread

ensemble - Variable in class ciir.umass.edu.learning.tree.LambdaMART

Ensemble - Class in ciir.umass.edu.learning.tree

Ensemble() - Constructor for class ciir.umass.edu.learning.tree.Ensemble

Ensemble(Ensemble) - Constructor for class ciir.umass.edu.learning.tree.Ensemble

Ensemble(String) - Constructor for class ciir.umass.edu.learning.tree.Ensemble

ensembles - Variable in class ciir.umass.edu.learning.tree.RFRanker

ERR - ciir.umass.edu.metric.METRIC

error - Variable in class ciir.umass.edu.learning.neuralnet.RankNet

ERRScorer - Class in ciir.umass.edu.metric

ERRScorer() - Constructor for class ciir.umass.edu.metric.ERRScorer

ERRScorer(int) - Constructor for class ciir.umass.edu.metric.ERRScorer

estimateLoss() - Method in class ciir.umass.edu.learning.neuralnet.LambdaRank

estimateLoss() - Method in class ciir.umass.edu.learning.neuralnet.ListNet

estimateLoss() - Method in class ciir.umass.edu.learning.neuralnet.RankNet

eval(DataPoint) - Method in class ciir.umass.edu.learning.boosting.AdaRank

eval(DataPoint) - Method in class ciir.umass.edu.learning.boosting.RankBoost

eval(DataPoint) - Method in class ciir.umass.edu.learning.CoorAscent

eval(DataPoint) - Method in class ciir.umass.edu.learning.LinearRegRank

eval(DataPoint) - Method in class ciir.umass.edu.learning.neuralnet.ListNet

eval(DataPoint) - Method in class ciir.umass.edu.learning.neuralnet.RankNet

eval(DataPoint) - Method in class ciir.umass.edu.learning.Ranker

eval(DataPoint) - Method in class ciir.umass.edu.learning.tree.Ensemble

eval(DataPoint) - Method in class ciir.umass.edu.learning.tree.LambdaMART

eval(DataPoint) - Method in class ciir.umass.edu.learning.tree.RegressionTree

Get the tree output for the input sample

eval(DataPoint) - Method in class ciir.umass.edu.learning.tree.RFRanker

eval(DataPoint) - Method in class ciir.umass.edu.learning.tree.Split

eval(String) - Method in class ciir.umass.edu.utilities.ExpressionEvaluator

evaluate(Ranker, List<RankList>) - Method in class ciir.umass.edu.eval.Evaluator

evaluate(String, double, String, String) - Method in class ciir.umass.edu.eval.Evaluator

Evaluate the currently selected ranking algorithm using percenTrain% of the training samples for training the rest as validation data.

evaluate(String, String, int, float, String, String) - Method in class ciir.umass.edu.eval.Evaluator

Evaluate the currently selected ranking algorithm using with k-fold cross validation.

evaluate(String, String, int, String, String) - Method in class ciir.umass.edu.eval.Evaluator

Evaluate the currently selected ranking algorithm using with k-fold cross validation.

evaluate(String, String, String, double) - Method in class ciir.umass.edu.eval.Evaluator

Evaluate the currently selected ranking algorithm using percenTrain% of the samples for training the rest for testing.

evaluate(String, String, String, String) - Method in class ciir.umass.edu.eval.Evaluator

Evaluate the currently selected ranking algorithm using .

Evaluator - Class in ciir.umass.edu.eval

Evaluator(RANKER_TYPE, METRIC, int) - Constructor for class ciir.umass.edu.eval.Evaluator

Evaluator(RANKER_TYPE, METRIC, int, METRIC, int) - Constructor for class ciir.umass.edu.eval.Evaluator

Evaluator(RANKER_TYPE, METRIC, METRIC) - Constructor for class ciir.umass.edu.eval.Evaluator

Evaluator(RANKER_TYPE, METRIC, METRIC, int) - Constructor for class ciir.umass.edu.eval.Evaluator

Evaluator(RANKER_TYPE, String, String) - Constructor for class ciir.umass.edu.eval.Evaluator

execute(WorkerThread, int) - Method in class ciir.umass.edu.utilities.MyThreadPool

execute(Runnable) - Method in class ciir.umass.edu.utilities.MyThreadPool

ExpressionEvaluator - Class in ciir.umass.edu.utilities

ExpressionEvaluator() - Constructor for class ciir.umass.edu.utilities.ExpressionEvaluator

F

FEATURE_INCREASE - Static variable in class ciir.umass.edu.learning.DataPoint

FeatureHistogram - Class in ciir.umass.edu.learning.tree

FeatureHistogram() - Constructor for class ciir.umass.edu.learning.tree.FeatureHistogram

FeatureManager - Class in ciir.umass.edu.features

FeatureManager() - Constructor for class ciir.umass.edu.features.FeatureManager

features - Variable in class ciir.umass.edu.learning.Ranker

features - Variable in class ciir.umass.edu.learning.tree.Ensemble

features - Variable in class ciir.umass.edu.learning.tree.FeatureHistogram

features - Variable in class ciir.umass.edu.learning.tree.RegressionTree

featureSamplingRate - Static variable in class ciir.umass.edu.learning.tree.RFRanker

FeatureStats - Class in ciir.umass.edu.features

FeatureStats(String) - Constructor for class ciir.umass.edu.features.FeatureStats

Define the saved model file to be used.

feedForward(RankList) - Method in class ciir.umass.edu.learning.neuralnet.ListNet

FileUtils - Class in ciir.umass.edu.utilities

This class provides some file processing utilities such as read/write files, obtain files in a directory...

FileUtils() - Constructor for class ciir.umass.edu.utilities.FileUtils

findBestSplit(int[], int, int, int) - Method in class ciir.umass.edu.learning.tree.FeatureHistogram

findBestSplit(Split, double[], int) - Method in class ciir.umass.edu.learning.tree.FeatureHistogram

fit() - Method in class ciir.umass.edu.learning.tree.RegressionTree

Fit the tree from the specified training data

fVals - Variable in class ciir.umass.edu.learning.DataPoint

G

gain - Static variable in class ciir.umass.edu.metric.DCGScorer

gain(int) - Method in class ciir.umass.edu.metric.DCGScorer

gcCycle - Static variable in class ciir.umass.edu.learning.tree.LambdaMART

get() - Method in class ciir.umass.edu.utilities.TmpFile

get(int) - Method in class ciir.umass.edu.learning.neuralnet.Layer

get(int) - Method in class ciir.umass.edu.learning.RankList

getAllFiles(String) - Static method in class ciir.umass.edu.utilities.FileUtils

Get all file (non-recursively) from a directory.

getAllFiles2(String) - Static method in class ciir.umass.edu.utilities.FileUtils

Get all file (non-recursively) from a directory.

getCached() - Method in class ciir.umass.edu.learning.DataPoint

getCorrectRanking() - Method in class ciir.umass.edu.learning.RankList

getDCG(int[], int) - Method in class ciir.umass.edu.metric.DCGScorer

getDescription() - Method in class ciir.umass.edu.learning.DataPoint

getDeviance() - Method in class ciir.umass.edu.learning.tree.Split

getEnsemble() - Method in class ciir.umass.edu.learning.tree.LambdaMART

getEnsembles() - Method in class ciir.umass.edu.learning.tree.RFRanker

getFeatureFromSampleVector(List<RankList>) - Static method in class ciir.umass.edu.features.FeatureManager

Obtain all features present in a sample set.

getFeatures() - Method in class ciir.umass.edu.learning.Ranker

getFeatures() - Method in class ciir.umass.edu.learning.tree.Ensemble

getFeatureValue(int) - Method in class ciir.umass.edu.learning.DataPoint

Get the value of the feature with the given feature ID

getFeatureValue(int) - Method in class ciir.umass.edu.learning.DenseDataPoint

getFeatureValue(int) - Method in class ciir.umass.edu.learning.SparseDataPoint

getFeatureVector() - Method in class ciir.umass.edu.learning.DataPoint

Gets the value of all features as a dense array of feature values.

getFeatureVector() - Method in class ciir.umass.edu.learning.DenseDataPoint

getFeatureVector() - Method in class ciir.umass.edu.learning.SparseDataPoint

getFid() - Method in class ciir.umass.edu.learning.boosting.RBWeakRanker

getFID() - Method in class ciir.umass.edu.learning.boosting.WeakRanker

getFileName(String) - Static method in class ciir.umass.edu.utilities.FileUtils

getID() - Method in class ciir.umass.edu.learning.DataPoint

getID() - Method in class ciir.umass.edu.learning.RankList

getInLinks() - Method in class ciir.umass.edu.learning.neuralnet.Neuron

getInstance() - Static method in class ciir.umass.edu.utilities.MyThreadPool

getK() - Method in class ciir.umass.edu.metric.MetricScorer

The depth parameter, or how deep of a ranked list to use to score the measure.

getKey(String) - Static method in class ciir.umass.edu.learning.DataPoint

getLabel() - Method in class ciir.umass.edu.learning.DataPoint

getLastWeightAdjustment() - Method in class ciir.umass.edu.learning.neuralnet.Synapse

getLeft() - Method in class ciir.umass.edu.learning.tree.Split

getNumberOfKnownFeatures() - Method in class ciir.umass.edu.learning.DataPoint

getOutLinks() - Method in class ciir.umass.edu.learning.neuralnet.Neuron

getOutput() - Method in class ciir.umass.edu.learning.neuralnet.Neuron

getOutput() - Method in class ciir.umass.edu.learning.tree.Split

getOutput(int) - Method in class ciir.umass.edu.learning.neuralnet.Neuron

getPath() - Method in class ciir.umass.edu.utilities.TmpFile

getRanking(short) - Method in class ciir.umass.edu.learning.RankList

getRelevanceLabels(RankList) - Method in class ciir.umass.edu.metric.MetricScorer

getRemains() - Method in class ciir.umass.edu.learning.Sampler

getRight() - Method in class ciir.umass.edu.learning.tree.Split

getRPN(String) - Method in class ciir.umass.edu.utilities.ExpressionEvaluator

getSamples() - Method in class ciir.umass.edu.learning.Sampler

getSamples() - Method in class ciir.umass.edu.learning.tree.Split

getSampleSortedIndex() - Method in class ciir.umass.edu.learning.tree.Split

getScoreOnTrainingData() - Method in class ciir.umass.edu.learning.Ranker

getScoreOnValidationData() - Method in class ciir.umass.edu.learning.Ranker

getSource() - Method in class ciir.umass.edu.learning.neuralnet.Synapse

getSqSumLabel() - Method in class ciir.umass.edu.learning.tree.Split

getString(String) - Method in class ciir.umass.edu.learning.tree.Split

getSumLabel() - Method in class ciir.umass.edu.learning.tree.Split

getTarget() - Method in class ciir.umass.edu.learning.neuralnet.Synapse

getThreshold() - Method in class ciir.umass.edu.learning.boosting.RBWeakRanker

getTrainingTime() - Method in class ciir.umass.edu.learning.RankerTrainer

getTree(int) - Method in class ciir.umass.edu.learning.tree.Ensemble

getValue(String) - Static method in class ciir.umass.edu.learning.DataPoint

getWeight() - Method in class ciir.umass.edu.learning.neuralnet.Synapse

getWeight(int) - Method in class ciir.umass.edu.learning.tree.Ensemble

getWriter() - Method in class ciir.umass.edu.utilities.TmpFile

H

hasFeature(int) - Method in class ciir.umass.edu.learning.SparseDataPoint

hist - Variable in class ciir.umass.edu.learning.tree.LambdaMART

hist - Variable in class ciir.umass.edu.learning.tree.RegressionTree

hist - Variable in class ciir.umass.edu.learning.tree.Split

HyperTangentFunction - Class in ciir.umass.edu.learning.neuralnet

HyperTangentFunction() - Constructor for class ciir.umass.edu.learning.neuralnet.HyperTangentFunction

I

id - Variable in class ciir.umass.edu.learning.DataPoint

idealGains - Variable in class ciir.umass.edu.metric.NDCGScorer

index - Variable in class ciir.umass.edu.learning.tree.RegressionTree

init() - Method in class ciir.umass.edu.learning.boosting.AdaRank

init() - Method in class ciir.umass.edu.learning.boosting.RankBoost

init() - Method in class ciir.umass.edu.learning.CoorAscent

init() - Method in class ciir.umass.edu.learning.LinearRegRank

init() - Method in class ciir.umass.edu.learning.neuralnet.ListNet

init() - Method in class ciir.umass.edu.learning.neuralnet.RankNet

Main public functions

init() - Method in class ciir.umass.edu.learning.Ranker

HAVE TO BE OVER-RIDDEN IN SUB-CLASSES

init() - Method in class ciir.umass.edu.learning.tree.LambdaMART

init() - Method in class ciir.umass.edu.learning.tree.RFRanker

init(int) - Static method in class ciir.umass.edu.utilities.MyThreadPool

inLinks - Variable in class ciir.umass.edu.learning.neuralnet.Neuron

inputLayer - Variable in class ciir.umass.edu.learning.neuralnet.RankNet

insert(List<Split>, Split) - Method in class ciir.umass.edu.learning.tree.RegressionTree

internalReorder(RankList) - Method in class ciir.umass.edu.learning.neuralnet.LambdaRank

internalReorder(RankList) - Method in class ciir.umass.edu.learning.neuralnet.RankNet

isRoot() - Method in class ciir.umass.edu.learning.tree.Split

isUnknown(float) - Static method in class ciir.umass.edu.learning.DataPoint

K

k - Variable in class ciir.umass.edu.metric.MetricScorer

The depth parameter, or how deep of a ranked list to use to score the measure.

keepOrigFeatures - Static variable in class ciir.umass.edu.eval.Evaluator

keys - Variable in class ciir.umass.edu.utilities.KeyValuePair

keys() - Method in class ciir.umass.edu.utilities.KeyValuePair

KeyValuePair - Class in ciir.umass.edu.utilities

KeyValuePair(String) - Constructor for class ciir.umass.edu.utilities.KeyValuePair

knownFeatures - Variable in class ciir.umass.edu.learning.DataPoint

L

label - Variable in class ciir.umass.edu.learning.DataPoint

labels - Variable in class ciir.umass.edu.learning.neuralnet.PropParameter

lambda - Static variable in class ciir.umass.edu.learning.LinearRegRank

LambdaMART - Class in ciir.umass.edu.learning.tree

LambdaMART() - Constructor for class ciir.umass.edu.learning.tree.LambdaMART

LambdaMART(List<RankList>, int[], MetricScorer) - Constructor for class ciir.umass.edu.learning.tree.LambdaMART

LAMBDAMART - ciir.umass.edu.learning.RANKER_TYPE

LambdaRank - Class in ciir.umass.edu.learning.neuralnet

LambdaRank() - Constructor for class ciir.umass.edu.learning.neuralnet.LambdaRank

LambdaRank(List<RankList>, int[], MetricScorer) - Constructor for class ciir.umass.edu.learning.neuralnet.LambdaRank

LAMBDARANK - ciir.umass.edu.learning.RANKER_TYPE

lastError - Variable in class ciir.umass.edu.learning.neuralnet.RankNet

lastTrainedScore - Variable in class ciir.umass.edu.learning.boosting.AdaRank

Layer - Class in ciir.umass.edu.learning.neuralnet

Layer(int) - Constructor for class ciir.umass.edu.learning.neuralnet.Layer

Layer(int, int) - Constructor for class ciir.umass.edu.learning.neuralnet.Layer

layers - Variable in class ciir.umass.edu.learning.neuralnet.RankNet

leafCount() - Method in class ciir.umass.edu.learning.tree.Ensemble

learn() - Method in class ciir.umass.edu.learning.boosting.AdaRank

learn() - Method in class ciir.umass.edu.learning.boosting.RankBoost

learn() - Method in class ciir.umass.edu.learning.CoorAscent

learn() - Method in class ciir.umass.edu.learning.LinearRegRank

learn() - Method in class ciir.umass.edu.learning.neuralnet.ListNet

learn() - Method in class ciir.umass.edu.learning.neuralnet.RankNet

learn() - Method in class ciir.umass.edu.learning.Ranker

learn() - Method in class ciir.umass.edu.learning.tree.LambdaMART

learn() - Method in class ciir.umass.edu.learning.tree.RFRanker

learningRate - Static variable in class ciir.umass.edu.learning.neuralnet.ListNet

learningRate - Static variable in class ciir.umass.edu.learning.neuralnet.Neuron

learningRate - Static variable in class ciir.umass.edu.learning.neuralnet.RankNet

learningRate - Static variable in class ciir.umass.edu.learning.tree.LambdaMART

learningRate - Static variable in class ciir.umass.edu.learning.tree.RFRanker

leaves - Variable in class ciir.umass.edu.learning.tree.RegressionTree

leaves() - Method in class ciir.umass.edu.learning.tree.RegressionTree

Retrieve all leave nodes in the tree

leaves() - Method in class ciir.umass.edu.learning.tree.Split

LINEAR_REGRESSION - ciir.umass.edu.learning.RANKER_TYPE

LinearNormalizer - Class in ciir.umass.edu.features

LinearNormalizer() - Constructor for class ciir.umass.edu.features.LinearNormalizer

LinearRegRank - Class in ciir.umass.edu.learning

LinearRegRank() - Constructor for class ciir.umass.edu.learning.LinearRegRank

LinearRegRank(List<RankList>, int[], MetricScorer) - Constructor for class ciir.umass.edu.learning.LinearRegRank

ListNet - Class in ciir.umass.edu.learning.neuralnet

ListNet() - Constructor for class ciir.umass.edu.learning.neuralnet.ListNet

ListNet(List<RankList>, int[], MetricScorer) - Constructor for class ciir.umass.edu.learning.neuralnet.ListNet

LISTNET - ciir.umass.edu.learning.RANKER_TYPE

ListNeuron - Class in ciir.umass.edu.learning.neuralnet

ListNeuron() - Constructor for class ciir.umass.edu.learning.neuralnet.ListNeuron

ln(double) - Static method in class ciir.umass.edu.utilities.SimpleMath

loadExternalRelevanceJudgment(String) - Method in class ciir.umass.edu.metric.APScorer

loadExternalRelevanceJudgment(String) - Method in class ciir.umass.edu.metric.MetricScorer

loadExternalRelevanceJudgment(String) - Method in class ciir.umass.edu.metric.NDCGScorer

loadFromString(String) - Method in class ciir.umass.edu.learning.boosting.AdaRank

loadFromString(String) - Method in class ciir.umass.edu.learning.boosting.RankBoost

loadFromString(String) - Method in class ciir.umass.edu.learning.CoorAscent

loadFromString(String) - Method in class ciir.umass.edu.learning.LinearRegRank

loadFromString(String) - Method in class ciir.umass.edu.learning.neuralnet.ListNet

loadFromString(String) - Method in class ciir.umass.edu.learning.neuralnet.RankNet

loadFromString(String) - Method in class ciir.umass.edu.learning.Ranker

loadFromString(String) - Method in class ciir.umass.edu.learning.tree.LambdaMART

loadFromString(String) - Method in class ciir.umass.edu.learning.tree.RFRanker

loadRankerFromFile(String) - Method in class ciir.umass.edu.learning.RankerFactory

loadRankerFromString(String) - Method in class ciir.umass.edu.learning.RankerFactory

logBase10(double) - Static method in class ciir.umass.edu.utilities.SimpleMath

logBase2(double) - Static method in class ciir.umass.edu.utilities.SimpleMath

LogiFunction - Class in ciir.umass.edu.learning.neuralnet

LogiFunction() - Constructor for class ciir.umass.edu.learning.neuralnet.LogiFunction

M

main(String[]) - Static method in class ciir.umass.edu.eval.Analyzer

main(String[]) - Static method in class ciir.umass.edu.eval.Evaluator

main(String[]) - Static method in class ciir.umass.edu.features.FeatureManager

main(String[]) - Static method in class ciir.umass.edu.learning.Combiner

main(String[]) - Static method in class ciir.umass.edu.utilities.ExpressionEvaluator

main(String[]) - Static method in class ciir.umass.edu.utilities.MergeSorter

makePathStandard(String) - Static method in class ciir.umass.edu.utilities.FileUtils

makeRCall() - Method in class ciir.umass.edu.stats.SignificanceTest

map - Static variable in class ciir.umass.edu.learning.RankerFactory

MAP - ciir.umass.edu.metric.METRIC

MART - Class in ciir.umass.edu.learning.tree

MART - ciir.umass.edu.learning.RANKER_TYPE

MART() - Constructor for class ciir.umass.edu.learning.tree.MART

MART(List<RankList>, int[], MetricScorer) - Constructor for class ciir.umass.edu.learning.tree.MART

martSamples - Variable in class ciir.umass.edu.learning.tree.LambdaMART

MAX - Static variable in class ciir.umass.edu.metric.ERRScorer

MAX_FEATURE - Static variable in class ciir.umass.edu.learning.DataPoint

maxSelCount - Static variable in class ciir.umass.edu.learning.boosting.AdaRank

maxToK(RankList, int) - Method in class ciir.umass.edu.metric.BestAtKScorer

Return the position of the best object (e.g.

mean(double[]) - Static method in class ciir.umass.edu.stats.BasicStats

MergeSorter - Class in ciir.umass.edu.utilities

MergeSorter() - Constructor for class ciir.umass.edu.utilities.MergeSorter

METRIC - Enum in ciir.umass.edu.metric

MetricScorer - Class in ciir.umass.edu.metric

MetricScorer() - Constructor for class ciir.umass.edu.metric.MetricScorer

MetricScorerFactory - Class in ciir.umass.edu.metric

MetricScorerFactory() - Constructor for class ciir.umass.edu.metric.MetricScorerFactory

mFact - Variable in class ciir.umass.edu.eval.Evaluator

min(int, int) - Static method in class ciir.umass.edu.utilities.SimpleMath

minLeafSupport - Static variable in class ciir.umass.edu.learning.tree.LambdaMART

minLeafSupport - Variable in class ciir.umass.edu.learning.tree.RegressionTree

minLeafSupport - Static variable in class ciir.umass.edu.learning.tree.RFRanker

misorderedPairs - Variable in class ciir.umass.edu.learning.neuralnet.RankNet

missingZero - Static variable in class ciir.umass.edu.learning.DataPoint

model() - Method in class ciir.umass.edu.learning.boosting.AdaRank

model() - Method in class ciir.umass.edu.learning.boosting.RankBoost

model() - Method in class ciir.umass.edu.learning.CoorAscent

model() - Method in class ciir.umass.edu.learning.LinearRegRank

model() - Method in class ciir.umass.edu.learning.neuralnet.ListNet

model() - Method in class ciir.umass.edu.learning.neuralnet.RankNet

model() - Method in class ciir.umass.edu.learning.Ranker

model() - Method in class ciir.umass.edu.learning.tree.LambdaMART

model() - Method in class ciir.umass.edu.learning.tree.RFRanker

modelFile - Static variable in class ciir.umass.edu.eval.Evaluator

modelScores - Variable in class ciir.umass.edu.learning.tree.LambdaMART

modelScoresOnValidation - Variable in class ciir.umass.edu.learning.tree.LambdaMART

momentum - Static variable in class ciir.umass.edu.learning.neuralnet.Neuron

mustHaveRelDoc - Static variable in class ciir.umass.edu.eval.Evaluator

MyThreadPool - Class in ciir.umass.edu.utilities

N

name() - Method in class ciir.umass.edu.features.LinearNormalizer

name() - Method in class ciir.umass.edu.features.Normalizer

name() - Method in class ciir.umass.edu.features.SumNormalizor

name() - Method in class ciir.umass.edu.features.ZScoreNormalizor

name() - Method in class ciir.umass.edu.learning.boosting.AdaRank

name() - Method in class ciir.umass.edu.learning.boosting.RankBoost

name() - Method in class ciir.umass.edu.learning.CoorAscent

name() - Method in class ciir.umass.edu.learning.LinearRegRank

name() - Method in class ciir.umass.edu.learning.neuralnet.LambdaRank

name() - Method in class ciir.umass.edu.learning.neuralnet.ListNet

name() - Method in class ciir.umass.edu.learning.neuralnet.RankNet

name() - Method in class ciir.umass.edu.learning.Ranker

name() - Method in class ciir.umass.edu.learning.tree.LambdaMART

name() - Method in class ciir.umass.edu.learning.tree.MART

name() - Method in class ciir.umass.edu.learning.tree.RFRanker

name() - Method in class ciir.umass.edu.metric.APScorer

name() - Method in class ciir.umass.edu.metric.BestAtKScorer

name() - Method in class ciir.umass.edu.metric.DCGScorer

name() - Method in class ciir.umass.edu.metric.ERRScorer

name() - Method in class ciir.umass.edu.metric.MetricScorer

name() - Method in class ciir.umass.edu.metric.NDCGScorer

name() - Method in class ciir.umass.edu.metric.PrecisionScorer

name() - Method in class ciir.umass.edu.metric.ReciprocalRankScorer

nBag - Static variable in class ciir.umass.edu.learning.tree.RFRanker

NDCG - ciir.umass.edu.metric.METRIC

NDCGScorer - Class in ciir.umass.edu.metric

NDCGScorer() - Constructor for class ciir.umass.edu.metric.NDCGScorer

NDCGScorer(int) - Constructor for class ciir.umass.edu.metric.NDCGScorer

Neuron - Class in ciir.umass.edu.learning.neuralnet

Neuron() - Constructor for class ciir.umass.edu.learning.neuralnet.Neuron

neurons - Variable in class ciir.umass.edu.learning.neuralnet.Layer

newFeatureFile - Static variable in class ciir.umass.edu.eval.Evaluator

nHiddenLayer - Static variable in class ciir.umass.edu.learning.neuralnet.ListNet

nHiddenLayer - Static variable in class ciir.umass.edu.learning.neuralnet.RankNet

nHiddenNodePerLayer - Static variable in class ciir.umass.edu.learning.neuralnet.RankNet

nIteration - Static variable in class ciir.umass.edu.learning.boosting.AdaRank

nIteration - Static variable in class ciir.umass.edu.learning.boosting.RankBoost

nIteration - Static variable in class ciir.umass.edu.learning.neuralnet.ListNet

nIteration - Static variable in class ciir.umass.edu.learning.neuralnet.RankNet

nMaxIteration - Static variable in class ciir.umass.edu.learning.CoorAscent

nml - Static variable in class ciir.umass.edu.eval.Evaluator

nodes - Variable in class ciir.umass.edu.learning.tree.RegressionTree

normalize - Static variable in class ciir.umass.edu.eval.Evaluator

normalize(RankList) - Method in class ciir.umass.edu.features.LinearNormalizer

normalize(RankList) - Method in class ciir.umass.edu.features.Normalizer

normalize(RankList) - Method in class ciir.umass.edu.features.SumNormalizor

normalize(RankList) - Method in class ciir.umass.edu.features.ZScoreNormalizor

normalize(RankList, int[]) - Method in class ciir.umass.edu.features.LinearNormalizer

normalize(RankList, int[]) - Method in class ciir.umass.edu.features.Normalizer

normalize(RankList, int[]) - Method in class ciir.umass.edu.features.SumNormalizor

normalize(RankList, int[]) - Method in class ciir.umass.edu.features.ZScoreNormalizor

normalize(List<RankList>) - Method in class ciir.umass.edu.eval.Evaluator

normalize(List<RankList>) - Method in class ciir.umass.edu.features.Normalizer

normalize(List<RankList>, int[]) - Method in class ciir.umass.edu.eval.Evaluator

normalize(List<RankList>, int[]) - Method in class ciir.umass.edu.features.Normalizer

normalizeAll(List<List<RankList>>, int[]) - Method in class ciir.umass.edu.eval.Evaluator

Normalizer - Class in ciir.umass.edu.features

Normalizer() - Constructor for class ciir.umass.edu.features.Normalizer

nPermutation - Static variable in class ciir.umass.edu.stats.RandomPermutationTest

nRestart - Static variable in class ciir.umass.edu.learning.CoorAscent

nRoundToStopEarly - Static variable in class ciir.umass.edu.learning.tree.LambdaMART

nThreshold - Static variable in class ciir.umass.edu.learning.boosting.RankBoost

nThreshold - Static variable in class ciir.umass.edu.learning.tree.LambdaMART

nThreshold - Static variable in class ciir.umass.edu.learning.tree.RFRanker

nTreeLeaves - Static variable in class ciir.umass.edu.learning.tree.LambdaMART

nTreeLeaves - Static variable in class ciir.umass.edu.learning.tree.RFRanker

nTrees - Static variable in class ciir.umass.edu.learning.tree.LambdaMART

nTrees - Static variable in class ciir.umass.edu.learning.tree.RFRanker

numFeatures(RankList) - Method in class ciir.umass.edu.features.Normalizer

O

outLinks - Variable in class ciir.umass.edu.learning.neuralnet.Neuron

output - Variable in class ciir.umass.edu.learning.neuralnet.Neuron

outputLayer - Variable in class ciir.umass.edu.learning.neuralnet.RankNet

outputs - Variable in class ciir.umass.edu.learning.neuralnet.Neuron

P

p(long, long) - Static method in class ciir.umass.edu.utilities.SimpleMath

pairMap - Variable in class ciir.umass.edu.learning.neuralnet.PropParameter

pairWeight - Variable in class ciir.umass.edu.learning.neuralnet.PropParameter

parse(String) - Method in class ciir.umass.edu.learning.DataPoint

Parse the given line of text to construct a dense array of feature values and reset metadata.

partition(int) - Method in class ciir.umass.edu.utilities.MyThreadPool

potential - Variable in class ciir.umass.edu.learning.boosting.RankBoost

Precision - ciir.umass.edu.metric.METRIC

PrecisionScorer - Class in ciir.umass.edu.metric

PrecisionScorer() - Constructor for class ciir.umass.edu.metric.PrecisionScorer

PrecisionScorer(int) - Constructor for class ciir.umass.edu.metric.PrecisionScorer

prepareCV(List<RankList>, int, float, List<List<RankList>>, List<List<RankList>>, List<List<RankList>>) - Static method in class ciir.umass.edu.features.FeatureManager

Split the input sample set into k chunks (folds) of roughly equal size and create train/test data for each fold.

prepareCV(List<RankList>, int, List<List<RankList>>, List<List<RankList>>) - Static method in class ciir.umass.edu.features.FeatureManager

Split the input sample set into k chunks (folds) of roughly equal size and create train/test data for each fold.

prepareSplit(List<RankList>, double, List<RankList>, List<RankList>) - Static method in class ciir.umass.edu.features.FeatureManager

Split the input sample set into 2 chunks: one for training and one for either validation or testing

PRINT(int[], String[]) - Method in class ciir.umass.edu.learning.Ranker

PRINT(String) - Method in class ciir.umass.edu.learning.Ranker

PRINT_MEMORY_USAGE() - Method in class ciir.umass.edu.learning.Ranker

PRINTLN(int[], String[]) - Method in class ciir.umass.edu.learning.Ranker

PRINTLN(String) - Method in class ciir.umass.edu.learning.Ranker

printNetworkConfig() - Method in class ciir.umass.edu.learning.neuralnet.RankNet

FOR DEBUGGING PURPOSE ONLY

printParameters() - Method in class ciir.umass.edu.learning.boosting.AdaRank

printParameters() - Method in class ciir.umass.edu.learning.boosting.RankBoost

printParameters() - Method in class ciir.umass.edu.learning.CoorAscent

printParameters() - Method in class ciir.umass.edu.learning.LinearRegRank

printParameters() - Method in class ciir.umass.edu.learning.neuralnet.ListNet

printParameters() - Method in class ciir.umass.edu.learning.neuralnet.RankNet

printParameters() - Method in class ciir.umass.edu.learning.Ranker

printParameters() - Method in class ciir.umass.edu.learning.tree.LambdaMART

printParameters() - Method in class ciir.umass.edu.learning.tree.RFRanker

printQueriesForSplit(String, List<List<RankList>>) - Static method in class ciir.umass.edu.features.FeatureManager

PRINTTIME() - Method in class ciir.umass.edu.learning.Ranker

printTrainingTime() - Method in class ciir.umass.edu.learning.RankerTrainer

printWeightVector() - Method in class ciir.umass.edu.learning.neuralnet.RankNet

propagate(int) - Method in class ciir.umass.edu.learning.neuralnet.RankNet

PropParameter - Class in ciir.umass.edu.learning.neuralnet

PropParameter(float[]) - Constructor for class ciir.umass.edu.learning.neuralnet.PropParameter

PropParameter(int, int[][]) - Constructor for class ciir.umass.edu.learning.neuralnet.PropParameter

PropParameter(int, int[][], float[][], float[][]) - Constructor for class ciir.umass.edu.learning.neuralnet.PropParameter

pseudoResponses - Variable in class ciir.umass.edu.learning.tree.LambdaMART

Q

qrelFile - Static variable in class ciir.umass.edu.eval.Evaluator

R

RANDOM_FOREST - ciir.umass.edu.learning.RANKER_TYPE

RandomPermutationTest - Class in ciir.umass.edu.stats

Randomized permutation test.

RandomPermutationTest() - Constructor for class ciir.umass.edu.stats.RandomPermutationTest

rank(int, int) - Method in class ciir.umass.edu.learning.tree.LambdaMART

This function is equivalent to the inherited function rank(...), but it uses the cached model's outputs instead of computing them from scratch.

rank(RankList) - Method in class ciir.umass.edu.learning.boosting.WeakRanker

rank(RankList) - Method in class ciir.umass.edu.learning.CoorAscent

rank(RankList) - Method in class ciir.umass.edu.learning.Ranker

rank(String, String) - Method in class ciir.umass.edu.eval.Evaluator

Generate a ranking in Indri's format from the input ranking

rank(String, String, String) - Method in class ciir.umass.edu.eval.Evaluator

Use a pre-trained model to re-rank the test rankings.

rank(List<RankList>) - Method in class ciir.umass.edu.learning.boosting.WeakRanker

rank(List<RankList>) - Method in class ciir.umass.edu.learning.Ranker

rank(List<String>, String, String) - Method in class ciir.umass.edu.eval.Evaluator

Use k pre-trained models to re-rank the test rankings.

rank(List<String>, List<String>, String) - Method in class ciir.umass.edu.eval.Evaluator

Similar to the above, except data has already been splitted.

RankBoost - Class in ciir.umass.edu.learning.boosting

RankBoost() - Constructor for class ciir.umass.edu.learning.boosting.RankBoost

RankBoost(List<RankList>, int[], MetricScorer) - Constructor for class ciir.umass.edu.learning.boosting.RankBoost

RANKBOOST - ciir.umass.edu.learning.RANKER_TYPE

Ranker - Class in ciir.umass.edu.learning

Ranker() - Constructor for class ciir.umass.edu.learning.Ranker

Ranker(List<RankList>, int[], MetricScorer) - Constructor for class ciir.umass.edu.learning.Ranker

RANKER_TYPE - Enum in ciir.umass.edu.learning

RankerFactory - Class in ciir.umass.edu.learning

RankerFactory() - Constructor for class ciir.umass.edu.learning.RankerFactory

rankers - Variable in class ciir.umass.edu.learning.boosting.AdaRank

RankerTrainer - Class in ciir.umass.edu.learning

RankerTrainer() - Constructor for class ciir.umass.edu.learning.RankerTrainer

RankLibError - Exception in ciir.umass.edu.utilities

Instead of using random error types, use RankLibError exceptions throughout -- this means that clients can catch-all from us easily.

RankList - Class in ciir.umass.edu.learning

RankList(RankList) - Constructor for class ciir.umass.edu.learning.RankList

RankList(RankList, int[]) - Constructor for class ciir.umass.edu.learning.RankList

RankList(RankList, int[], int) - Constructor for class ciir.umass.edu.learning.RankList

RankList(List<DataPoint>) - Constructor for class ciir.umass.edu.learning.RankList

RankNet - Class in ciir.umass.edu.learning.neuralnet

RankNet() - Constructor for class ciir.umass.edu.learning.neuralnet.RankNet

RankNet(List<RankList>, int[], MetricScorer) - Constructor for class ciir.umass.edu.learning.neuralnet.RankNet

RANKNET - ciir.umass.edu.learning.RANKER_TYPE

RBWeakRanker - Class in ciir.umass.edu.learning.boosting

RBWeakRanker(int, double) - Constructor for class ciir.umass.edu.learning.boosting.RBWeakRanker

read(String) - Method in class ciir.umass.edu.eval.Analyzer

Read performance (in some measure of effectiveness) file.

read(String, String) - Static method in class ciir.umass.edu.utilities.FileUtils

Read the content of a file.

readFeature(String) - Method in class ciir.umass.edu.eval.Evaluator

readFeature(String) - Static method in class ciir.umass.edu.features.FeatureManager

Read features specified in an input feature file.

readInput(String) - Method in class ciir.umass.edu.eval.Evaluator

readInput(String) - Static method in class ciir.umass.edu.features.FeatureManager

Read a set of rankings from a single file.

readInput(String, boolean, boolean) - Static method in class ciir.umass.edu.features.FeatureManager

Read a set of rankings from a single file.

readInput(List<String>) - Static method in class ciir.umass.edu.features.FeatureManager

Read sets of rankings from multiple files.

readLine(String, String) - Static method in class ciir.umass.edu.utilities.FileUtils

Reciprocal - ciir.umass.edu.metric.METRIC

ReciprocalRankScorer - Class in ciir.umass.edu.metric

ReciprocalRankScorer() - Constructor for class ciir.umass.edu.metric.ReciprocalRankScorer

RegressionTree - Class in ciir.umass.edu.learning.tree

RegressionTree(int, DataPoint[], double[], FeatureHistogram, int) - Constructor for class ciir.umass.edu.learning.tree.RegressionTree

RegressionTree(Split) - Constructor for class ciir.umass.edu.learning.tree.RegressionTree

regularized - Static variable in class ciir.umass.edu.learning.CoorAscent

relDocCount - Variable in class ciir.umass.edu.metric.APScorer

remains - Variable in class ciir.umass.edu.learning.Sampler

remove(int) - Method in class ciir.umass.edu.learning.tree.Ensemble

removeDuplicateFeatures(int[]) - Method in class ciir.umass.edu.features.Normalizer

resetCached() - Method in class ciir.umass.edu.learning.DataPoint

restoreBestModelOnValidation() - Method in class ciir.umass.edu.learning.neuralnet.RankNet

rf - Variable in class ciir.umass.edu.learning.RankerTrainer

rFact - Variable in class ciir.umass.edu.eval.Evaluator

rFactory - Variable in class ciir.umass.edu.learning.RankerFactory

RFRanker - Class in ciir.umass.edu.learning.tree

RFRanker() - Constructor for class ciir.umass.edu.learning.tree.RFRanker

RFRanker(List<RankList>, int[], MetricScorer) - Constructor for class ciir.umass.edu.learning.tree.RFRanker

rl - Variable in class ciir.umass.edu.learning.RankList

root - Variable in class ciir.umass.edu.learning.tree.RegressionTree

round(double) - Static method in class ciir.umass.edu.utilities.SimpleMath

round(double, int) - Static method in class ciir.umass.edu.utilities.SimpleMath

round(float) - Static method in class ciir.umass.edu.utilities.SimpleMath

round(float, int) - Static method in class ciir.umass.edu.utilities.SimpleMath

rType - Static variable in class ciir.umass.edu.learning.tree.RFRanker

rweight - Variable in class ciir.umass.edu.learning.boosting.AdaRank

rWeight - Variable in class ciir.umass.edu.learning.boosting.RankBoost

S

Sampler - Class in ciir.umass.edu.learning

Sampler() - Constructor for class ciir.umass.edu.learning.Sampler

samples - Variable in class ciir.umass.edu.learning.Ranker

samples - Variable in class ciir.umass.edu.learning.Sampler

samples - Variable in class ciir.umass.edu.learning.tree.Split

sampleToThresholdMap - Variable in class ciir.umass.edu.learning.tree.FeatureHistogram

samplingRate - Static variable in class ciir.umass.edu.learning.tree.FeatureHistogram

save(String) - Method in class ciir.umass.edu.learning.Ranker

save(List<RankList>, String) - Static method in class ciir.umass.edu.features.FeatureManager

Save a sample set to file

saveBestModelOnValidation() - Method in class ciir.umass.edu.learning.neuralnet.RankNet

Model validation

savePerRankListPerformanceFile(List<String>, List<Double>, String) - Method in class ciir.umass.edu.eval.Evaluator

Save systems' performance to file

score(DataPoint) - Method in class ciir.umass.edu.learning.boosting.RBWeakRanker

score(RankList) - Method in class ciir.umass.edu.metric.APScorer

Compute Average Precision (AP) of the list.

score(RankList) - Method in class ciir.umass.edu.metric.BestAtKScorer

score(RankList) - Method in class ciir.umass.edu.metric.DCGScorer

Compute DCG at k.

score(RankList) - Method in class ciir.umass.edu.metric.ERRScorer

Compute ERR at k.

score(RankList) - Method in class ciir.umass.edu.metric.MetricScorer

score(RankList) - Method in class ciir.umass.edu.metric.NDCGScorer

Compute NDCG at k.

score(RankList) - Method in class ciir.umass.edu.metric.PrecisionScorer

score(RankList) - Method in class ciir.umass.edu.metric.ReciprocalRankScorer

score(String, String, String) - Method in class ciir.umass.edu.eval.Evaluator

Write the model's score for each of the documents in a test rankings.

score(List<RankList>) - Method in class ciir.umass.edu.metric.MetricScorer

score(List<String>, String, String) - Method in class ciir.umass.edu.eval.Evaluator

Write the models' score for each of the documents in a test rankings.

score(List<String>, List<String>, String) - Method in class ciir.umass.edu.eval.Evaluator

Similar to the above, except data has already been split.

scoreOnTrainingData - Variable in class ciir.umass.edu.learning.Ranker

scorer - Variable in class ciir.umass.edu.learning.Ranker

set(int, float, double) - Method in class ciir.umass.edu.learning.tree.Split

set(int, int) - Method in class ciir.umass.edu.utilities.WorkerThread

set(int, DataPoint) - Method in class ciir.umass.edu.learning.RankList

setCached(double) - Method in class ciir.umass.edu.learning.DataPoint

setDescription(String) - Method in class ciir.umass.edu.learning.DataPoint

setFeatures(int[]) - Method in class ciir.umass.edu.learning.Ranker

setFeatureValue(int, float) - Method in class ciir.umass.edu.learning.DataPoint

Set the value of the feature with the given feature ID

setFeatureValue(int, float) - Method in class ciir.umass.edu.learning.DenseDataPoint

setFeatureValue(int, float) - Method in class ciir.umass.edu.learning.SparseDataPoint

setFeatureVector(float[]) - Method in class ciir.umass.edu.learning.DataPoint

Sets the value of all features with the provided dense array of feature values

setFeatureVector(float[]) - Method in class ciir.umass.edu.learning.DenseDataPoint

setFeatureVector(float[]) - Method in class ciir.umass.edu.learning.SparseDataPoint

setID(String) - Method in class ciir.umass.edu.learning.DataPoint

setInputOutput(int, int) - Method in class ciir.umass.edu.learning.neuralnet.RankNet

Setting up the Neural Network

setInputOutput(int, int, int) - Method in class ciir.umass.edu.learning.neuralnet.RankNet

setK(int) - Method in class ciir.umass.edu.metric.MetricScorer

The depth parameter, or how deep of a ranked list to use to score the measure.

setLabel(float) - Method in class ciir.umass.edu.learning.DataPoint

setLeft(Split) - Method in class ciir.umass.edu.learning.tree.Split

setMetricScorer(MetricScorer) - Method in class ciir.umass.edu.learning.Ranker

setOutput(double) - Method in class ciir.umass.edu.learning.neuralnet.Neuron

setOutput(float) - Method in class ciir.umass.edu.learning.tree.Split

setRight(Split) - Method in class ciir.umass.edu.learning.tree.Split

setRoot(boolean) - Method in class ciir.umass.edu.learning.tree.Split

setTrainingSet(List<RankList>) - Method in class ciir.umass.edu.learning.Ranker

setValidationSet(List<RankList>) - Method in class ciir.umass.edu.learning.Ranker

setWeight(double) - Method in class ciir.umass.edu.learning.neuralnet.Synapse

setWeightAdjustment(double) - Method in class ciir.umass.edu.learning.neuralnet.Synapse

SignificanceTest - Class in ciir.umass.edu.stats

SignificanceTest() - Constructor for class ciir.umass.edu.stats.SignificanceTest

SimpleMath - Class in ciir.umass.edu.utilities

SimpleMath() - Constructor for class ciir.umass.edu.utilities.SimpleMath

size() - Method in class ciir.umass.edu.learning.neuralnet.Layer

size() - Method in class ciir.umass.edu.learning.RankList

size() - Method in class ciir.umass.edu.utilities.MyThreadPool

slack - Static variable in class ciir.umass.edu.learning.CoorAscent

smartReader(String) - Static method in class ciir.umass.edu.utilities.FileUtils

smartReader(String, String) - Static method in class ciir.umass.edu.utilities.FileUtils

solve(double[][], double[]) - Method in class ciir.umass.edu.learning.LinearRegRank

Solve a system of linear equations Ax=B, in which A has to be a square matrix with the same length as B

sort(double[], boolean) - Static method in class ciir.umass.edu.utilities.MergeSorter

sort(double[], boolean) - Static method in class ciir.umass.edu.utilities.Sorter

Sort a double array using Interchange sort.

sort(double[], int, int, boolean) - Static method in class ciir.umass.edu.utilities.MergeSorter

sort(float[], boolean) - Static method in class ciir.umass.edu.utilities.MergeSorter

sort(float[], boolean) - Static method in class ciir.umass.edu.utilities.Sorter

sort(float[], int, int, boolean) - Static method in class ciir.umass.edu.utilities.MergeSorter

sort(int[], boolean) - Static method in class ciir.umass.edu.utilities.Sorter

Sort an integer array using Quick Sort.

sort(List<Integer>, boolean) - Static method in class ciir.umass.edu.utilities.Sorter

Sort an integer array using Quick Sort.

sortDesc(List<Double>) - Static method in class ciir.umass.edu.utilities.Sorter

Sort an double array using Quick Sort.

sortedIdx - Variable in class ciir.umass.edu.learning.tree.LambdaMART

sortedSamples - Variable in class ciir.umass.edu.learning.boosting.RankBoost

Sorter - Class in ciir.umass.edu.utilities

This class contains the implementation of some simple sorting algorithms.

Sorter() - Constructor for class ciir.umass.edu.utilities.Sorter

sortLong(List<Long>, boolean) - Static method in class ciir.umass.edu.utilities.Sorter

Sort an long array using Quick Sort.

sortSamplesByFeature(int, int) - Method in class ciir.umass.edu.learning.tree.LambdaMART

sortSamplesByFeature(DataPoint[], int) - Method in class ciir.umass.edu.learning.tree.LambdaMART

sortString(List<String>, boolean) - Static method in class ciir.umass.edu.utilities.Sorter

source - Variable in class ciir.umass.edu.learning.neuralnet.Synapse

SparseDataPoint - Class in ciir.umass.edu.learning

Implements a sparse data point using a compressed sparse row data structure

SparseDataPoint(float[], int[], String, float) - Constructor for class ciir.umass.edu.learning.SparseDataPoint

Allows the direct allocation of a SparseDataPoint instead of having it parse text.

SparseDataPoint(SparseDataPoint) - Constructor for class ciir.umass.edu.learning.SparseDataPoint

SparseDataPoint(String) - Constructor for class ciir.umass.edu.learning.SparseDataPoint

split(double[], int) - Method in class ciir.umass.edu.learning.tree.Split

Split - Class in ciir.umass.edu.learning.tree

Split() - Constructor for class ciir.umass.edu.learning.tree.Split

Split(int[][], double, double, double) - Constructor for class ciir.umass.edu.learning.tree.Split

Split(int[], FeatureHistogram, double, double) - Constructor for class ciir.umass.edu.learning.tree.Split

Split(int, float, double) - Constructor for class ciir.umass.edu.learning.tree.Split

sqSumResponse - Variable in class ciir.umass.edu.learning.tree.FeatureHistogram

start - Variable in class ciir.umass.edu.utilities.WorkerThread

stepBase - Static variable in class ciir.umass.edu.learning.CoorAscent

stepScale - Static variable in class ciir.umass.edu.learning.CoorAscent

straightLoss - Variable in class ciir.umass.edu.learning.neuralnet.RankNet

subSamplingRate - Static variable in class ciir.umass.edu.learning.tree.RFRanker

sum - Variable in class ciir.umass.edu.learning.tree.FeatureHistogram

SumNormalizor - Class in ciir.umass.edu.features

SumNormalizor() - Constructor for class ciir.umass.edu.features.SumNormalizor

sumResponse - Variable in class ciir.umass.edu.learning.tree.FeatureHistogram

swapChange(RankList) - Method in class ciir.umass.edu.metric.APScorer

swapChange(RankList) - Method in class ciir.umass.edu.metric.BestAtKScorer

swapChange(RankList) - Method in class ciir.umass.edu.metric.DCGScorer

swapChange(RankList) - Method in class ciir.umass.edu.metric.ERRScorer

swapChange(RankList) - Method in class ciir.umass.edu.metric.MetricScorer

swapChange(RankList) - Method in class ciir.umass.edu.metric.NDCGScorer

swapChange(RankList) - Method in class ciir.umass.edu.metric.PrecisionScorer

swapChange(RankList) - Method in class ciir.umass.edu.metric.ReciprocalRankScorer

sweight - Variable in class ciir.umass.edu.learning.boosting.AdaRank

sweight - Variable in class ciir.umass.edu.learning.boosting.RankBoost

Synapse - Class in ciir.umass.edu.learning.neuralnet

Synapse(Neuron, Neuron) - Constructor for class ciir.umass.edu.learning.neuralnet.Synapse

T

target - Variable in class ciir.umass.edu.learning.neuralnet.Synapse

targetValue - Variable in class ciir.umass.edu.learning.neuralnet.LambdaRank

targetValue - Variable in class ciir.umass.edu.learning.neuralnet.PropParameter

test(String) - Method in class ciir.umass.edu.eval.Evaluator

Evaluate the performance (in -metric2T) of the input rankings

test(String, String) - Method in class ciir.umass.edu.eval.Evaluator

test(String, String, String) - Method in class ciir.umass.edu.eval.Evaluator

Evaluate the performance (in -metric2T) of a pre-trained model.

test(HashMap<String, Double>, HashMap<String, Double>) - Method in class ciir.umass.edu.stats.RandomPermutationTest

Run the randomization test

test(HashMap<String, Double>, HashMap<String, Double>) - Method in class ciir.umass.edu.stats.SignificanceTest

test(List<String>, String, String) - Method in class ciir.umass.edu.eval.Evaluator

Evaluate the performance (in -metric2T) of k pre-trained models.

test(List<String>, List<String>, String) - Method in class ciir.umass.edu.eval.Evaluator

Similar to the above, except data has already been splitted.

testScorer - Variable in class ciir.umass.edu.eval.Evaluator

testWithScoreFile(String, String) - Method in class ciir.umass.edu.eval.Evaluator

Re-order the input rankings and measure their effectiveness (in -metric2T)

tfunc - Variable in class ciir.umass.edu.learning.neuralnet.Neuron

thresholds - Variable in class ciir.umass.edu.learning.boosting.RankBoost

thresholds - Variable in class ciir.umass.edu.learning.tree.FeatureHistogram

thresholds - Variable in class ciir.umass.edu.learning.tree.LambdaMART

thresholds - Variable in class ciir.umass.edu.learning.tree.RegressionTree

TmpFile - Class in ciir.umass.edu.utilities

TmpFile() - Constructor for class ciir.umass.edu.utilities.TmpFile

tolerance - Static variable in class ciir.umass.edu.learning.boosting.AdaRank

tolerance - Static variable in class ciir.umass.edu.learning.CoorAscent

topNew - Static variable in class ciir.umass.edu.eval.Evaluator

toString() - Method in class ciir.umass.edu.learning.boosting.AdaRank

toString() - Method in class ciir.umass.edu.learning.boosting.RankBoost

toString() - Method in class ciir.umass.edu.learning.boosting.RBWeakRanker

toString() - Method in class ciir.umass.edu.learning.CoorAscent

toString() - Method in class ciir.umass.edu.learning.DataPoint

toString() - Method in class ciir.umass.edu.learning.LinearRegRank

toString() - Method in class ciir.umass.edu.learning.neuralnet.ListNet

toString() - Method in class ciir.umass.edu.learning.neuralnet.RankNet

toString() - Method in class ciir.umass.edu.learning.Ranker

toString() - Method in class ciir.umass.edu.learning.tree.Ensemble

toString() - Method in class ciir.umass.edu.learning.tree.LambdaMART

toString() - Method in class ciir.umass.edu.learning.tree.RegressionTree

Generate the string representation of the tree

toString() - Method in class ciir.umass.edu.learning.tree.RFRanker

toString() - Method in class ciir.umass.edu.learning.tree.Split

toString(String) - Method in class ciir.umass.edu.learning.tree.RegressionTree

toString(String) - Method in class ciir.umass.edu.learning.tree.Split

totalPairs - Variable in class ciir.umass.edu.learning.neuralnet.RankNet

train(RANKER_TYPE, List<RankList>, int[], MetricScorer) - Method in class ciir.umass.edu.learning.RankerTrainer

train(RANKER_TYPE, List<RankList>, List<RankList>, int[], MetricScorer) - Method in class ciir.umass.edu.learning.RankerTrainer

trainingLabels - Variable in class ciir.umass.edu.learning.tree.RegressionTree

trainingSamples - Variable in class ciir.umass.edu.learning.tree.RegressionTree

trainingTime - Variable in class ciir.umass.edu.learning.RankerTrainer

trainScorer - Variable in class ciir.umass.edu.eval.Evaluator

trainWithEnqueue - Static variable in class ciir.umass.edu.learning.boosting.AdaRank

TransferFunction - Interface in ciir.umass.edu.learning.neuralnet

treeCount() - Method in class ciir.umass.edu.learning.tree.Ensemble

trees - Variable in class ciir.umass.edu.learning.tree.Ensemble

tSortedIdx - Variable in class ciir.umass.edu.learning.boosting.RankBoost

type - Variable in class ciir.umass.edu.eval.Evaluator

U

UNKNOWN - Static variable in class ciir.umass.edu.learning.DataPoint

update(double[]) - Method in class ciir.umass.edu.learning.tree.FeatureHistogram

update(double[], int, int) - Method in class ciir.umass.edu.learning.tree.FeatureHistogram

updateDelta(PropParameter) - Method in class ciir.umass.edu.learning.neuralnet.Layer

Update delta from neurons in the previous layers

updateDelta(PropParameter) - Method in class ciir.umass.edu.learning.neuralnet.Neuron

Update delta from neurons in the next layer (back-propagate)

updateTreeOutput(RegressionTree) - Method in class ciir.umass.edu.learning.tree.LambdaMART

updateTreeOutput(RegressionTree) - Method in class ciir.umass.edu.learning.tree.MART

updateWeight() - Method in class ciir.umass.edu.learning.neuralnet.Synapse

updateWeight(PropParameter) - Method in class ciir.umass.edu.learning.neuralnet.Layer

updateWeight(PropParameter) - Method in class ciir.umass.edu.learning.neuralnet.ListNeuron

updateWeight(PropParameter) - Method in class ciir.umass.edu.learning.neuralnet.Neuron

Update weights of incoming links.

usedFeatures - Variable in class ciir.umass.edu.learning.boosting.AdaRank

useSparseRepresentation - Static variable in class ciir.umass.edu.eval.Evaluator

V

validationSamples - Variable in class ciir.umass.edu.learning.Ranker

valueOf(String) - Static method in enum ciir.umass.edu.learning.RANKER_TYPE

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum ciir.umass.edu.metric.METRIC

Returns the enum constant of this type with the specified name.

values - Variable in class ciir.umass.edu.utilities.KeyValuePair

values() - Static method in enum ciir.umass.edu.learning.RANKER_TYPE

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum ciir.umass.edu.metric.METRIC

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Method in class ciir.umass.edu.utilities.KeyValuePair

variance() - Method in class ciir.umass.edu.learning.tree.Ensemble

variance() - Method in class ciir.umass.edu.learning.tree.RegressionTree

verbose - Static variable in class ciir.umass.edu.learning.Ranker

W

WeakRanker - Class in ciir.umass.edu.learning.boosting

WeakRanker(int) - Constructor for class ciir.umass.edu.learning.boosting.WeakRanker

weight - Variable in class ciir.umass.edu.learning.CoorAscent

weight - Variable in class ciir.umass.edu.learning.LinearRegRank

weight - Variable in class ciir.umass.edu.learning.neuralnet.Synapse

weight_change - Variable in class ciir.umass.edu.learning.CoorAscent

weights - Variable in class ciir.umass.edu.learning.tree.Ensemble

weights - Variable in class ciir.umass.edu.learning.tree.LambdaMART

wire() - Method in class ciir.umass.edu.learning.neuralnet.RankNet

WorkerThread - Class in ciir.umass.edu.utilities

WorkerThread() - Constructor for class ciir.umass.edu.utilities.WorkerThread

wRankers - Variable in class ciir.umass.edu.learning.boosting.RankBoost

write(String, String, String) - Static method in class ciir.umass.edu.utilities.FileUtils

Write a text to a file.

writeFeatureStats() - Method in class ciir.umass.edu.features.FeatureStats

Z

ZScoreNormalizor - Class in ciir.umass.edu.features

ZScoreNormalizor() - Constructor for class ciir.umass.edu.features.ZScoreNormalizor

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