A B C D E F G I J K L M N O P R S T U V W X

A

ACCURACY - Static variable in class edu.mit.util.stats.Results
 
accuracy() - Method in class edu.mit.util.stats.Results
 
addCounts(double[]) - Method in class edu.mit.nlp.segmenter.Segment
 
addCountsForSentence(int, int) - Method in class edu.mit.nlp.segmenter.mcmc.CuCoSeg
addCountsForSentence i -- the document j -- the sentenec uses the segs[] variable: complexity: K[i] + N[i][j], where K is the number of segs, and N[i][j] is the number of words in sent j
addToCounts(double[], int[], double) - Static method in class edu.mit.util.ling.CountsManager
 
addToCounts(double[], int[], double, int, int) - Static method in class edu.mit.util.ling.CountsManager
 
addToCounts(int[], int[], int) - Static method in class edu.mit.util.ling.CountsManager
 
addToCounts(int[], int[], int, int, int) - Static method in class edu.mit.util.ling.CountsManager
 
addToCountsFirst(double[], int[], double) - Static method in class edu.mit.util.ling.CountsManager
 
addToCountsFirst(int[], int[], int) - Static method in class edu.mit.util.ling.CountsManager
 
addToCountsRest(double[], int[], double) - Static method in class edu.mit.util.ling.CountsManager
 
addToCountsRest(int[], int[], int) - Static method in class edu.mit.util.ling.CountsManager
 
all_accuracy() - Method in class edu.mit.util.stats.ResultTracker
 
all_falseAlarm() - Method in class edu.mit.util.stats.ResultTracker
 
all_fMeasure() - Method in class edu.mit.util.stats.ResultTracker
 
all_precision() - Method in class edu.mit.util.stats.ResultTracker
 
all_recall() - Method in class edu.mit.util.stats.ResultTracker
 
anneal(double) - Method in class edu.mit.util.stats.Annealer
calls the annealer, adds one tick
Annealer - Class in edu.mit.util.stats
 
Annealer(double, double, double, int) - Constructor for class edu.mit.util.stats.Annealer
 
annealWithoutUpdate(double) - Method in class edu.mit.util.stats.Annealer
 
averageRepeatedMeasures() - Method in class edu.mit.util.stats.ResultTracker
 

B

BayesWrapper - Class in edu.mit.nlp.segmenter.dp
Wraps the dynamic programming Bayesian segmenter DPSeg, so that it can be called by SegTester
BayesWrapper() - Constructor for class edu.mit.nlp.segmenter.dp.BayesWrapper
 

C

changeCountsForSentence(int, int, int) - Method in class edu.mit.nlp.segmenter.mcmc.CuCoSeg
 
combine(Results) - Method in class edu.mit.util.stats.Results
 
combine(Results, Results) - Static method in class edu.mit.util.stats.Results
 
combine(Results) - Method in class edu.mit.util.stats.ResultTracker
 
combine(ResultTracker) - Method in class edu.mit.util.stats.ResultTracker
 
computeCueLogProb() - Method in class edu.mit.nlp.segmenter.mcmc.CuCoSeg
computeCueLogProb() computes the log-likelihood of the cue phrase counts
computeDispersionGradient(int, double, double, FastDigamma) - Static method in class edu.mit.util.stats.Stats
 
computeGradient(double[]) - Method in class edu.mit.nlp.segmenter.dp.DPSeg
computes the gradient of the likelihood, across the whole dataset.
computeGradientForSegment(int[], double, double, FastDigamma) - Method in class edu.mit.nlp.segmenter.mcmc.CuCoSeg.PriorOptimizer
 
computeLogMultinomial(double[], double) - Static method in class edu.mit.util.stats.Stats
 
computeLogProb() - Method in class edu.mit.nlp.segmenter.mcmc.CuCoSeg
computes the overall log probability
computeLogProb(int, int) - Method in class edu.mit.nlp.segmenter.mcmc.CuCoSeg
computes the portion of the log-probability associated with a change to segment seg in doc considers the b-counts, o-counts, and the i-counts for seg, seg-1, and seg+1 (where applicable)
computeMultinomial(double[], double) - Static method in class edu.mit.util.stats.Stats
computeMultinomial builds the expected multinomial given counts and a symmetric dirichlet theta = argmax_theta p(theta | counts, prior) = argmax_theta p(counts | theta) p(theta | prior) this is in closed form due to conjugacy
computePDur(int, double, double) - Method in class edu.mit.nlp.segmenter.dp.DPSeg
 
computeTotalLL(double[]) - Method in class edu.mit.nlp.segmenter.dp.DPSeg
compute the loglikelihood for the whole dataset.
computeXtraProb() - Method in class edu.mit.nlp.segmenter.mcmc.CuCoSeg
 
CountsManager - Class in edu.mit.util.ling
 
CountsManager() - Constructor for class edu.mit.util.ling.CountsManager
 
createSparseWordOccurrenceTable() - Method in class edu.mit.nlp.MyTextWrapper
 
createSparseWordOccurrenceTable(LexMap) - Method in class edu.mit.nlp.MyTextWrapper
 
createWordOccurrenceTable(LexMap) - Method in class edu.mit.nlp.MyTextWrapper
 
createWordOccurrenceTable(List) - Method in class edu.mit.nlp.MyTextWrapper
 
CuCoSeg - Class in edu.mit.nlp.segmenter.mcmc
CuCoSeg -- Cue-phrase + Cohesion Segmentation Loads a second copy of all texts, from which stop words are not removed (because stopwords are sometimes good cues) Keeps a separate LexMap for each document.
CuCoSeg() - Constructor for class edu.mit.nlp.segmenter.mcmc.CuCoSeg
 
CuCoSeg.PriorOptimizer - Class in edu.mit.nlp.segmenter.mcmc
An LBFGS optimizer to search the parameter space
CuCoSeg.PriorOptimizer() - Constructor for class edu.mit.nlp.segmenter.mcmc.CuCoSeg.PriorOptimizer
 

D

D() - Method in class edu.mit.nlp.segmenter.Document
 
D2() - Method in class edu.mit.nlp.segmenter.Document
 
debug - Variable in class edu.mit.nlp.segmenter.dp.BayesWrapper
 
digamma(double) - Method in class edu.mit.util.stats.FastDigamma
 
dispersion - Variable in class edu.mit.nlp.segmenter.dp.BayesWrapper
 
Document - Class in edu.mit.nlp.segmenter
Keeps track of counts and segments.
Document(double[][], int) - Constructor for class edu.mit.nlp.segmenter.Document
 
DPDocument - Class in edu.mit.nlp.segmenter.dp
Extends Document with some methods specifically for the DP implementation of Bayesian segmentation.
DPDocument(double[][], int, boolean) - Constructor for class edu.mit.nlp.segmenter.dp.DPDocument
 
DPSeg - Class in edu.mit.nlp.segmenter.dp
This class implements the dynamic programming Bayesian segmentation, for both DCM and MAP language models.
DPSeg(DPDocument[][], int[][]) - Constructor for class edu.mit.nlp.segmenter.dp.DPSeg
 
DPSeg.PriorOptimizer - Class in edu.mit.nlp.segmenter.dp
A class for LBFGS optimization of the priors
DPSeg.PriorOptimizer() - Constructor for class edu.mit.nlp.segmenter.dp.DPSeg.PriorOptimizer
 

E

edu.mit.nlp - package edu.mit.nlp
 
edu.mit.nlp.segmenter - package edu.mit.nlp.segmenter
 
edu.mit.nlp.segmenter.dp - package edu.mit.nlp.segmenter.dp
 
edu.mit.nlp.segmenter.mcmc - package edu.mit.nlp.segmenter.mcmc
 
edu.mit.nlp.segmenter.wrappers - package edu.mit.nlp.segmenter.wrappers
 
edu.mit.util - package edu.mit.util
 
edu.mit.util.ling - package edu.mit.util.ling
 
edu.mit.util.stats - package edu.mit.util.stats
 
edu.mit.util.weka - package edu.mit.util.weka
 
em_params - Variable in class edu.mit.nlp.segmenter.dp.BayesWrapper
 
eval(Segmenter) - Method in class edu.mit.nlp.segmenter.SegTester
Evaluate a segmenter.
evaluateGradient(double[]) - Method in class edu.mit.nlp.segmenter.dp.DPSeg.PriorOptimizer
 
evaluateGradient(double[]) - Method in class edu.mit.nlp.segmenter.mcmc.CuCoSeg.PriorOptimizer
assumes params are in log form
evaluateGradient(double[]) - Method in class edu.mit.util.weka.LBFGSWrapper
 

F

false_negatives - Variable in class edu.mit.util.stats.Results
 
false_positives - Variable in class edu.mit.util.stats.Results
 
falseAlarm() - Method in class edu.mit.util.stats.Results
 
FastDCM - Class in edu.mit.util.stats
 
FastDCM(double, int) - Constructor for class edu.mit.util.stats.FastDCM
 
FastDCM(double, int, boolean) - Constructor for class edu.mit.util.stats.FastDCM
 
FastDCM(double, int, FastGamma) - Constructor for class edu.mit.util.stats.FastDCM
 
FastDigamma - Class in edu.mit.util.stats
 
FastDigamma() - Constructor for class edu.mit.util.stats.FastDigamma
 
FastDigamma(int, float) - Constructor for class edu.mit.util.stats.FastDigamma
 
FastDoubleGamma - Class in edu.mit.util.stats
 
FastDoubleGamma() - Constructor for class edu.mit.util.stats.FastDoubleGamma
 
FastDoubleGamma(int, float) - Constructor for class edu.mit.util.stats.FastDoubleGamma
 
FastGamma - Interface in edu.mit.util.stats
 
FastIntGamma - Class in edu.mit.util.stats
 
FastIntGamma(int) - Constructor for class edu.mit.util.stats.FastIntGamma
 
FastIntGamma(int, double) - Constructor for class edu.mit.util.stats.FastIntGamma
 
findArgmin() - Method in class edu.mit.util.weka.LBFGSWrapper
 
FMEASURE - Static variable in class edu.mit.util.stats.Results
 
fMeasure() - Method in class edu.mit.util.stats.Results
 
formatArray(String, String, double[]) - Static method in class edu.mit.util.JacobUtil
 
formatArray(String, String, int[]) - Static method in class edu.mit.util.JacobUtil
 
formatArray(String, String[]) - Static method in class edu.mit.util.JacobUtil
 

G

gamma(double) - Method in class edu.mit.util.stats.FastDoubleGamma
 
gamma(double) - Method in interface edu.mit.util.stats.FastGamma
 
gamma(double) - Method in class edu.mit.util.stats.FastIntGamma
 
generateOrderings(List<T>) - Static method in class edu.mit.util.stats.Stats
 
getAvgResult(SegResult[]) - Static method in class edu.mit.nlp.segmenter.SegResult
 
getAvgResult(SegResult[], int) - Static method in class edu.mit.nlp.segmenter.SegResult
 
getBoolProp(Properties, String, boolean) - Static method in class edu.mit.nlp.segmenter.SegTesterParams
 
getDigamma() - Method in class edu.mit.nlp.segmenter.dp.DPDocument
 
getDoubleProp(Properties, String, double) - Static method in class edu.mit.nlp.segmenter.SegTesterParams
 
getDur() - Method in class edu.mit.nlp.segmenter.Segment
 
getGamma() - Method in class edu.mit.nlp.segmenter.dp.DPDocument
 
getGamma() - Method in class edu.mit.util.stats.FastDCM
 
getHalfProbAnnealed() - Method in class edu.mit.util.stats.Annealer
returns f(.5) given the current temp.
getIntProp(Properties, String, int) - Static method in class edu.mit.nlp.segmenter.SegTesterParams
 
getMinFunction() - Method in class edu.mit.util.weka.LBFGSWrapper
 
getMoveProposal(int, int) - Method in class edu.mit.nlp.segmenter.mcmc.CuCoSeg
generates an empirical distribution over moves of a given segmentation point
getNumArray(String) - Static method in class edu.mit.util.JacobUtil
 
getNumSegs(MyTextWrapper[]) - Static method in class edu.mit.nlp.MyTextWrapper
 
getOffset() - Method in class edu.mit.util.stats.FastIntGamma
 
getParaData(String) - Static method in class edu.mit.nlp.segmenter.SegTester
gets "paralinguistic" data, e.g. pause durations and prosodic markers.
getParams() - Method in class edu.mit.nlp.segmenter.dp.BayesWrapper
 
getParams() - Method in class edu.mit.nlp.segmenter.dp.DPSeg
 
getPauses() - Method in class edu.mit.nlp.ParaData
 
getPrior() - Method in class edu.mit.util.stats.FastDCM
 
getProps() - Method in class edu.mit.nlp.segmenter.SegTesterParams
 
getResponses() - Method in class edu.mit.nlp.segmenter.dp.DPSeg
get the segmentations
getSortedUnigrams(LexMap, int[], int[]) - Method in class edu.mit.nlp.segmenter.mcmc.CuCoSeg
 
getSpeakerChange() - Method in class edu.mit.nlp.ParaData
 
getSPs() - Method in class edu.mit.nlp.segmenter.Document
 
getString(ArrayList<Double>) - Method in class edu.mit.util.stats.ResultTracker
 
getTheta() - Method in class edu.mit.nlp.segmenter.Segment
 
getThetas() - Method in class edu.mit.nlp.segmenter.Document
 
getTrueSegs(TextWrapper) - Static method in class edu.mit.nlp.segmenter.dp.I2JInterface
 
getUseStems() - Method in class edu.mit.nlp.MyTextWrapper
 
getUseTags() - Method in class edu.mit.nlp.MyTextWrapper
 
getVarbValues() - Method in class edu.mit.util.weka.LBFGSWrapper
 
getWindowSize() - Method in class edu.mit.nlp.segmenter.SegTesterParams
 
getZHat(int[], int[]) - Static method in class edu.mit.nlp.segmenter.SegEval
 
getZStar(int[]) - Static method in class edu.mit.nlp.segmenter.SegEval
 

I

I2JInterface - Class in edu.mit.nlp.segmenter.dp
class for converting between my segmenter's data structures, and those from Igor's MinCutSeg
I2JInterface() - Constructor for class edu.mit.nlp.segmenter.dp.I2JInterface
 
InitializableSegmenter - Interface in edu.mit.nlp.segmenter
 
initialize(String) - Method in class edu.mit.nlp.segmenter.dp.BayesWrapper
 
initialize(String) - Method in class edu.mit.nlp.segmenter.mcmc.CuCoSeg
 
initialize(String) - Method in class edu.mit.nlp.segmenter.PerfectSegmenter
 
initialize(String) - Method in interface edu.mit.nlp.segmenter.Segmenter
Do whatever initialize you need from this config file
initialize(String) - Method in class edu.mit.nlp.segmenter.wrappers.LCSegWrapper
 
initialize(String) - Method in class edu.mit.nlp.segmenter.wrappers.MCSWrapper
 
initialize(String) - Method in class edu.mit.nlp.segmenter.wrappers.UIWrapper
 
initialize(int, double) - Method in class edu.mit.util.stats.FastIntGamma
 
initSegs(String) - Method in interface edu.mit.nlp.segmenter.InitializableSegmenter
 
initSegs(String) - Method in class edu.mit.nlp.segmenter.mcmc.CuCoSeg
initSegs -- load initial segmentation guesses from a file.
is_windowing_enabled - Variable in class edu.mit.nlp.segmenter.dp.BayesWrapper
 
isRemoveStopWords() - Method in class edu.mit.nlp.segmenter.SegTesterParams
 
isStemsEnabled() - Method in class edu.mit.nlp.segmenter.SegTesterParams
 
isWindowingEnabled() - Method in class edu.mit.nlp.segmenter.SegTesterParams
 

J

JacobUtil - Class in edu.mit.util
 
JacobUtil() - Constructor for class edu.mit.util.JacobUtil
 

K

kldiv(double[], double[]) - Static method in class edu.mit.util.stats.Stats
Computes the KL divergence of the distribution.

L

LBFGSWrapper - Class in edu.mit.util.weka
 
LBFGSWrapper(int) - Constructor for class edu.mit.util.weka.LBFGSWrapper
 
LCSegWrapper - Class in edu.mit.nlp.segmenter.wrappers
wraps the LCSeg segmenter
LCSegWrapper() - Constructor for class edu.mit.nlp.segmenter.wrappers.LCSegWrapper
 
learned_params - Variable in class edu.mit.nlp.segmenter.dp.BayesWrapper
 
loadFiles(OptionSet) - Method in class edu.mit.nlp.segmenter.SegTester
 
loadText(String) - Method in class edu.mit.nlp.segmenter.SegTester
 
logDCM(double[]) - Method in class edu.mit.util.stats.FastDCM
 
logDCM(int[]) - Method in class edu.mit.util.stats.FastDCM
 
logGamma(double) - Method in class edu.mit.util.stats.FastDoubleGamma
 
logGamma(double) - Method in interface edu.mit.util.stats.FastGamma
 
logGamma(double) - Method in class edu.mit.util.stats.FastIntGamma
 
logProbLogMultinomial(double[], double[]) - Static method in class edu.mit.util.stats.Stats
 
logProbMultinomial(double[], double[]) - Static method in class edu.mit.util.stats.Stats
computes the log-probability of a bag-of-words observation x, given the multinomial probability distribution a

M

m_dcm - Variable in class edu.mit.nlp.segmenter.dp.DPDocument
 
m_debug - Variable in class edu.mit.nlp.segmenter.dp.DPSeg
 
m_debug - Variable in class edu.mit.util.weka.LBFGSWrapper
 
m_eps - Variable in class edu.mit.util.weka.LBFGSWrapper
 
m_estimate - Variable in class edu.mit.util.weka.LBFGSWrapper
 
m_int_counts - Variable in class edu.mit.nlp.segmenter.dp.DPDocument
 
m_max_its - Variable in class edu.mit.util.weka.LBFGSWrapper
 
m_num_corrections - Variable in class edu.mit.util.weka.LBFGSWrapper
 
m_num_parameters - Variable in class edu.mit.util.weka.LBFGSWrapper
 
m_value - Variable in class edu.mit.util.weka.LBFGSWrapper
 
m_words - Variable in class edu.mit.nlp.segmenter.Document
 
main(String[]) - Static method in class edu.mit.nlp.segmenter.dp.DPDocument
Just does a unit test on some stuff
main(String[]) - Static method in class edu.mit.nlp.segmenter.SegEval
 
main(String[]) - Static method in class edu.mit.nlp.segmenter.SegTester
 
main(String[]) - Static method in class edu.mit.util.JacobUtil
 
main(String[]) - Static method in class edu.mit.util.stats.ResultTracker
 
main(String[]) - Static method in class edu.mit.util.stats.Stats
 
makeCumulCounts() - Method in class edu.mit.nlp.segmenter.dp.DPDocument
Builds up the cumulative counts, a representation that facilitates fast computation later.
makeDoubleArray(ArrayList<Double>) - Method in class edu.mit.util.stats.ResultTracker
 
makeDPDoc(TextWrapper) - Static method in class edu.mit.nlp.segmenter.dp.I2JInterface
 
makeIgorList(int[], TextWrapper, boolean) - Static method in class edu.mit.nlp.segmenter.dp.I2JInterface
 
makeListFormattedResponse(int[]) - Static method in class edu.mit.nlp.segmenter.dp.I2JInterface
 
matlabString() - Method in class edu.mit.util.stats.ResultTracker
 
MAX_LOG_DISPERSION - Static variable in class edu.mit.util.stats.Stats
 
MCSWrapper - Class in edu.mit.nlp.segmenter.wrappers
 
MCSWrapper() - Constructor for class edu.mit.nlp.segmenter.wrappers.MCSWrapper
 
mean(double[]) - Method in class edu.mit.util.stats.ResultTracker
 
minkaApprox(int[]) - Method in class edu.mit.nlp.segmenter.mcmc.CuCoSeg
sets the prior on the cue phrase language model, using the approximation proposed by Minka in "Estimating a Dirichlet Distribution" (eq 114)
myLogGammaPdf(double, double, double) - Static method in class edu.mit.util.stats.Stats
 
myLogNBinPdf(int, double, double) - Static method in class edu.mit.util.stats.Stats
 
myLogNBinPdf2(int, double, double) - Static method in class edu.mit.util.stats.Stats
 
MyTextWrapper - Class in edu.mit.nlp
 
MyTextWrapper(String) - Constructor for class edu.mit.nlp.MyTextWrapper
 

N

N() - Method in class edu.mit.nlp.segmenter.Document
 
num_hits - Variable in class edu.mit.util.stats.FastDigamma
 
num_hits - Variable in class edu.mit.util.stats.FastDoubleGamma
 
num_misses - Variable in class edu.mit.util.stats.FastDigamma
 
num_misses - Variable in class edu.mit.util.stats.FastDoubleGamma
 
num_segs_known - Variable in class edu.mit.nlp.segmenter.dp.BayesWrapper
 

O

objectiveFunction(double[]) - Method in class edu.mit.nlp.segmenter.dp.DPSeg.PriorOptimizer
 
objectiveFunction(double[]) - Method in class edu.mit.nlp.segmenter.mcmc.CuCoSeg.PriorOptimizer
assumes params are in log form
objectiveFunction(double[]) - Method in class edu.mit.util.weka.LBFGSWrapper
 

P

pairedTTest(ResultTracker, ResultTracker) - Static method in class edu.mit.util.stats.ResultTracker
outputs t-score that the distributions of fmeasures are different.
para_ending - Static variable in class edu.mit.nlp.segmenter.SegTester
 
ParaData - Class in edu.mit.nlp
Stores paralingual data: whether there's a speaker change between each turn silence between each turn maybe other stuffs later
ParaData(File) - Constructor for class edu.mit.nlp.ParaData
 
parse(boolean) - Method in class edu.mit.nlp.MyTextWrapper
 
parseWindows(int, boolean) - Method in class edu.mit.nlp.MyTextWrapper
 
PerfectSegmenter - Class in edu.mit.nlp.segmenter
for testing the evaluation -- returns the perfect segmentation
PerfectSegmenter() - Constructor for class edu.mit.nlp.segmenter.PerfectSegmenter
 
pkEval(int[], int[]) - Static method in class edu.mit.nlp.segmenter.SegEval
 
precision() - Method in class edu.mit.util.stats.Results
 
preprocessText(MyTextWrapper, boolean, boolean, boolean, boolean, int) - Static method in class edu.mit.nlp.segmenter.SegTester
does some preprocessing stuff on the text -- stemming, removing stop words, handling segment boundries, and breaking the text into K-word blocks.
printDurs() - Method in class edu.mit.nlp.segmenter.Document
print the durations of each segment.
printResults(PrintStream, SegResult[], double[]) - Static method in class edu.mit.nlp.segmenter.SegResult
 
printSegs() - Method in class edu.mit.nlp.segmenter.dp.DPSeg
 
printStatus(PrintStream, int) - Method in class edu.mit.nlp.segmenter.mcmc.CuCoSeg
prints a status message.
prior - Variable in class edu.mit.nlp.segmenter.dp.BayesWrapper
 

R

recall() - Method in class edu.mit.util.stats.Results
 
reset() - Method in class edu.mit.util.stats.Annealer
 
Results - Class in edu.mit.util.stats
 
Results() - Constructor for class edu.mit.util.stats.Results
 
ResultTracker - Class in edu.mit.util.stats
Tracks SegmentResults across multiple runs or trials or whatever...
ResultTracker() - Constructor for class edu.mit.util.stats.ResultTracker
 

S

scanParams(double[]) - Method in class edu.mit.nlp.segmenter.mcmc.CuCoSeg.PriorOptimizer
 
score(int) - Method in class edu.mit.util.stats.Results
 
segDCMGradient(int, int, double) - Method in class edu.mit.nlp.segmenter.dp.DPDocument
compute the gradient of the log-likelihood for a segment, under the DCM model
segEM(double[]) - Method in class edu.mit.nlp.segmenter.dp.DPSeg
segEM estimates the parameters using a form of hard EM it computes the best segmentation given the current parameters, then does a gradient-based search for new parameters, and iterates.
SegEval - Class in edu.mit.nlp.segmenter
 
SegEval() - Constructor for class edu.mit.nlp.segmenter.SegEval
 
segLL(int, int, double) - Method in class edu.mit.nlp.segmenter.dp.DPDocument
compute the log-likelihood of a segment
segLLDCM(int, int, double) - Method in class edu.mit.nlp.segmenter.dp.DPDocument
compute the log likelihood of a segment under the DCM model
segLLExp(int, int, double) - Method in class edu.mit.nlp.segmenter.dp.DPDocument
compute the log-likelihood of a segment, given the log of the prior
segLLGradientExp(int, int, double) - Method in class edu.mit.nlp.segmenter.dp.DPDocument
compute the gradient of the log-likelihood for a segment, under the DCM model
segLLMAP(int, int, double) - Method in class edu.mit.nlp.segmenter.dp.DPDocument
compute the log likelihood of a segment under the MAP language model
segMAPGradient(int, int, double) - Method in class edu.mit.nlp.segmenter.dp.DPDocument
compute the gradient of the log-likelihood for a segment, under the MAP language model.
segment(double[]) - Method in class edu.mit.nlp.segmenter.dp.DPSeg
segment each document in the dataset.
Segment - Class in edu.mit.nlp.segmenter
 
Segment(int) - Constructor for class edu.mit.nlp.segmenter.Segment
 
Segment(Segment) - Constructor for class edu.mit.nlp.segmenter.Segment
 
Segmenter - Interface in edu.mit.nlp.segmenter
If you want to have a segmenter be evaluated in SegTester, you must write a wrapper that implements this interface.
segmenter() - Method in class edu.mit.nlp.segmenter.SegTesterParams
 
segmentKnown(double[]) - Method in class edu.mit.nlp.segmenter.dp.DPSeg
segment in the case that the number of segments per doc is known. same arguments as DPSeg.segment(double[])
segmentTexts(MyTextWrapper[], int[]) - Method in class edu.mit.nlp.segmenter.dp.BayesWrapper
 
segmentTexts(MyTextWrapper[], int[]) - Method in class edu.mit.nlp.segmenter.mcmc.CuCoSeg
massively long method that segments all the texts
segmentTexts(MyTextWrapper[], int[]) - Method in class edu.mit.nlp.segmenter.PerfectSegmenter
 
segmentTexts(MyTextWrapper[]) - Method in class edu.mit.nlp.segmenter.PerfectSegmenter
 
segmentTexts(MyTextWrapper[], int[]) - Method in interface edu.mit.nlp.segmenter.Segmenter
segment a bunch of texts.
segmentTexts(MyTextWrapper[], int[]) - Method in class edu.mit.nlp.segmenter.wrappers.LCSegWrapper
 
segmentTexts(MyTextWrapper[], int[]) - Method in class edu.mit.nlp.segmenter.wrappers.MCSWrapper
 
segmentTexts(MyTextWrapper[], int[]) - Method in class edu.mit.nlp.segmenter.wrappers.UIWrapper
 
segmentUnknown(double[]) - Method in class edu.mit.nlp.segmenter.dp.DPSeg
segment in the case of an unknown number of segments. same arguments as DPSeg.segment(double[])
SegResult - Class in edu.mit.nlp.segmenter
 
SegResult(int[], int[], double) - Constructor for class edu.mit.nlp.segmenter.SegResult
 
SegResult() - Constructor for class edu.mit.nlp.segmenter.SegResult
 
SegTester - Class in edu.mit.nlp.segmenter
The purpose of this class is to provide a unified framework to evaluate and run various segmenters.
SegTester(OptionSet) - Constructor for class edu.mit.nlp.segmenter.SegTester
 
SegTesterParams - Class in edu.mit.nlp.segmenter
 
SegTesterParams(File) - Constructor for class edu.mit.nlp.segmenter.SegTesterParams
 
SegTesterParams(Properties) - Constructor for class edu.mit.nlp.segmenter.SegTesterParams
 
setDCMPrior(FastDCM, double) - Method in class edu.mit.nlp.segmenter.mcmc.CuCoSeg
Set the symmetric prior on the DCM language models
setDebug(boolean) - Method in class edu.mit.nlp.segmenter.dp.BayesWrapper
 
setDebug(boolean) - Method in class edu.mit.nlp.segmenter.mcmc.CuCoSeg
 
setDebug(boolean) - Method in class edu.mit.nlp.segmenter.PerfectSegmenter
 
setDebug(boolean) - Method in interface edu.mit.nlp.segmenter.Segmenter
tells your d00d to set its debug flag
setDebug(boolean) - Method in class edu.mit.nlp.segmenter.wrappers.LCSegWrapper
 
setDebug(boolean) - Method in class edu.mit.nlp.segmenter.wrappers.MCSWrapper
 
setDebug(boolean) - Method in class edu.mit.nlp.segmenter.wrappers.UIWrapper
 
setDebug(boolean) - Method in class edu.mit.util.weka.LBFGSWrapper
 
setDigamma(FastDigamma) - Method in class edu.mit.nlp.segmenter.dp.DPDocument
If you have multiple documents, you might want to share the cache for the digamma function across all documents.
setEstimate(double[]) - Method in class edu.mit.util.weka.LBFGSWrapper
setEstimate Use this to initialize the search
setGamma(FastGamma) - Method in class edu.mit.nlp.segmenter.dp.DPDocument
If you have multiple documents, you might want to share the cache for the gamma function across all documents.
setGamma(FastGamma) - Method in class edu.mit.util.stats.FastDCM
 
setMaxIteration(int) - Method in class edu.mit.util.weka.LBFGSWrapper
 
setOffset(double) - Method in class edu.mit.util.stats.FastIntGamma
 
setPDur(double[]) - Method in class edu.mit.nlp.segmenter.Document
 
setPDur(double[]) - Method in class edu.mit.nlp.segmenter.Segment
 
setPDurs() - Method in class edu.mit.nlp.segmenter.mcmc.CuCoSeg
Since durations are discrete, we keep a cache of the probability of each duration length.
setPrior(double) - Method in class edu.mit.nlp.segmenter.dp.DPDocument
 
setPrior(double) - Method in class edu.mit.util.stats.FastDCM
 
size() - Method in class edu.mit.util.stats.ResultTracker
 
Stats - Class in edu.mit.util.stats
 
Stats() - Constructor for class edu.mit.util.stats.Stats
 
stemStopWords(List) - Static method in class edu.mit.nlp.segmenter.SegTester
if we're doing stemming, then we need to also stem the stopwords (otherwise they won't match) This does that.
subCounts(double[]) - Method in class edu.mit.nlp.segmenter.Segment
 
subCountsForSentence(int, int) - Method in class edu.mit.nlp.segmenter.mcmc.CuCoSeg
 

T

T() - Method in class edu.mit.nlp.segmenter.Document
 
texts - Variable in class edu.mit.nlp.segmenter.SegTester
 
toDoubleArray(ArrayList<Double>) - Static method in class edu.mit.util.stats.ResultTracker
 
toString() - Method in class edu.mit.nlp.segmenter.SegResult
 
toString() - Method in class edu.mit.util.stats.Results
 
toString() - Method in class edu.mit.util.stats.ResultTracker
 
total() - Method in class edu.mit.util.stats.Results
 
true_negatives - Variable in class edu.mit.util.stats.Results
 
true_positives - Variable in class edu.mit.util.stats.Results
 

U

UIWrapper - Class in edu.mit.nlp.segmenter.wrappers
wraps the Utiyama & Isahara segmenter
UIWrapper() - Constructor for class edu.mit.nlp.segmenter.wrappers.UIWrapper
 
update() - Method in class edu.mit.util.stats.Annealer
 
updateCounts(int) - Method in class edu.mit.nlp.segmenter.mcmc.CuCoSeg
update the counts given a new lambda parameter
updateSegmentation(int, int, int) - Method in class edu.mit.nlp.segmenter.mcmc.CuCoSeg
update the segmentation move the segpt in the doc by the amount will update segs[] and also all the counts
use_duration - Variable in class edu.mit.nlp.segmenter.dp.BayesWrapper
 
useChoiStyleBounds() - Method in class edu.mit.nlp.segmenter.SegTesterParams
 
useTags() - Method in class edu.mit.nlp.MyTextWrapper
 

V

validMove(List, int, int) - Static method in class edu.mit.nlp.segmenter.mcmc.CuCoSeg
assesses whether a given move is valid (doesn't cross segment boundaries)
variance(double[]) - Method in class edu.mit.util.stats.ResultTracker
 

W

wdEval(int[], int[]) - Static method in class edu.mit.nlp.segmenter.SegEval
 

X

xtol - Variable in class edu.mit.util.weka.LBFGSWrapper
 

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