| Modifier and Type | Method and Description |
|---|---|
Instance |
Classification.getInstance() |
| Modifier and Type | Method and Description |
|---|---|
Classification |
Winnow.classify(Instance instance)
Classifies an instance using Winnow's weights
|
Classification |
NaiveBayes.classify(Instance instance)
Classify an instance using NaiveBayes according to the trained data.
|
Classification |
MaxEnt.classify(Instance instance) |
Classification |
MCMaxEnt.classify(Instance instance) |
Classification |
DecisionTree.classify(Instance instance) |
Classification |
ConfidencePredictingClassifier.classify(Instance instance) |
abstract Classification |
Classifier.classify(Instance instance) |
Classification |
C45.classify(Instance instance) |
Classification |
BalancedWinnow.classify(Instance instance)
Classifies an instance using BalancedWinnow's weights
|
Classification |
BaggingClassifier.classify(Instance inst) |
Classification |
AdaBoostM2.classify(Instance inst) |
Classification |
AdaBoost.classify(Instance inst) |
Classification[] |
Classifier.classify(Instance[] instances) |
Classification |
AdaBoostM2.classify(Instance inst,
int numWeakClassifiersToUse)
Classify the given instance using only the first
numWeakClassifiersToUse classifiers
trained during boosting
|
Classification |
AdaBoost.classify(Instance inst,
int numWeakClassifiersToUse)
Classify the given instance using only the first
numWeakClassifiersToUse classifiers
trained during boosting
|
void |
MaxEnt.getClassificationScores(Instance instance,
double[] scores) |
void |
MCMaxEnt.getClassificationScores(Instance instance,
double[] scores) |
void |
MaxEnt.getUnnormalizedClassificationScores(Instance instance,
double[] scores) |
void |
MCMaxEnt.getUnnormalizedClassificationScores(Instance instance,
double[] scores) |
| Constructor and Description |
|---|
Classification(Instance instance,
Classifier classifier,
Labeling labeling) |
| Modifier and Type | Method and Description |
|---|---|
Instance |
TokenSequence2Tokenization.pipe(Instance carrier) |
| Modifier and Type | Method and Description |
|---|---|
Instance |
TokenSequence2Tokenization.pipe(Instance carrier) |
| Modifier and Type | Method and Description |
|---|---|
Instance |
Transducer.pipe(Instance carrier)
We aren't really a Pipe subclass, but this method works like Pipes' do.
|
Instance |
SimpleTagger.SimpleTaggerSentence2FeatureVectorSequence.pipe(Instance carrier) |
| Modifier and Type | Method and Description |
|---|---|
Instance |
Transducer.pipe(Instance carrier)
We aren't really a Pipe subclass, but this method works like Pipes' do.
|
Instance |
SimpleTagger.SimpleTaggerSentence2FeatureVectorSequence.pipe(Instance carrier) |
| Modifier and Type | Method and Description |
|---|---|
Instance |
SequenceConfidenceInstance.getInstance() |
Instance |
PipedInstanceWithConfidence.getInstance() |
Instance |
InstanceWithConfidence.getInstance() |
| Modifier and Type | Method and Description |
|---|---|
double |
ViterbiRatioConfidenceEstimator.estimateConfidenceFor(Instance instance,
Object[] startTags,
Object[] inTags)
Calculates the confidence in the tagging of an
Instance. |
double |
ViterbiConfidenceEstimator.estimateConfidenceFor(Instance instance,
Object[] startTags,
Object[] inTags)
Calculates the confidence in the tagging of a
Instance. |
abstract double |
TransducerSequenceConfidenceEstimator.estimateConfidenceFor(Instance instance,
Object[] startTags,
Object[] inTags)
Calculates the confidence in the tagging of a
Sequence. |
double |
SegmentProductConfidenceEstimator.estimateConfidenceFor(Instance instance,
Object[] startTags,
Object[] inTags)
Calculates the confidence in the tagging of a
Instance. |
double |
RandomSequenceConfidenceEstimator.estimateConfidenceFor(Instance instance,
Object[] startTags,
Object[] inTags)
Calculates the confidence in the tagging of an
Instance. |
double |
NBestViterbiConfidenceEstimator.estimateConfidenceFor(Instance instance,
Object[] startTags,
Object[] inTags)
Calculates the confidence in the tagging of a
Instance. |
double |
MinSegmentConfidenceEstimator.estimateConfidenceFor(Instance instance,
Object[] startTags,
Object[] inTags)
Calculates the confidence in the tagging of a
Instance. |
double |
MaxEntSequenceConfidenceEstimator.estimateConfidenceFor(Instance instance,
Object[] startTags,
Object[] inTags)
Calculates the confidence in the tagging of an
Instance. |
Segment[] |
TransducerConfidenceEstimator.rankSegmentsByConfidence(Instance instance,
Object[] startTags,
Object[] continueTags)
ranks the segments in one
Instance |
| Constructor and Description |
|---|
InstanceWithConfidence(Instance inst,
double c,
boolean correct) |
InstanceWithConfidence(Instance inst,
double c,
Sequence predicted) |
PipedInstanceWithConfidence(Instance inst,
double c,
boolean correct) |
SequenceConfidenceInstance(Instance inst) |
| Modifier and Type | Method and Description |
|---|---|
Instance |
TestMEMM.TestMEMMTokenSequenceRemoveSpaces.pipe(Instance carrier) |
Instance |
TestMEMM.TestMEMM2String.pipe(Instance carrier) |
Instance |
TestCRF4.TestCRFTokenSequenceRemoveSpaces.pipe(Instance carrier) |
Instance |
TestCRF4.TestCRF2String.pipe(Instance carrier) |
Instance |
TestCRF3.TestCRFTokenSequenceRemoveSpaces.pipe(Instance carrier) |
Instance |
TestCRF3.TestCRF2String.pipe(Instance carrier) |
Instance |
TestCRF2.TestCRFTokenSequenceRemoveSpaces.pipe(Instance carrier) |
Instance |
TestCRF2.TestCRF2String.pipe(Instance carrier) |
Instance |
TestCRF.TestCRFTokenSequenceRemoveSpaces.pipe(Instance carrier) |
Instance |
TestCRF.TestCRF2String.pipe(Instance carrier) |
| Modifier and Type | Method and Description |
|---|---|
Instance |
TestMEMM.TestMEMMTokenSequenceRemoveSpaces.pipe(Instance carrier) |
Instance |
TestMEMM.TestMEMM2String.pipe(Instance carrier) |
Instance |
TestCRF4.TestCRFTokenSequenceRemoveSpaces.pipe(Instance carrier) |
Instance |
TestCRF4.TestCRF2String.pipe(Instance carrier) |
Instance |
TestCRF3.TestCRFTokenSequenceRemoveSpaces.pipe(Instance carrier) |
Instance |
TestCRF3.TestCRF2String.pipe(Instance carrier) |
Instance |
TestCRF2.TestCRFTokenSequenceRemoveSpaces.pipe(Instance carrier) |
Instance |
TestCRF2.TestCRF2String.pipe(Instance carrier) |
Instance |
TestCRF.TestCRFTokenSequenceRemoveSpaces.pipe(Instance carrier) |
Instance |
TestCRF.TestCRF2String.pipe(Instance carrier) |
| Modifier and Type | Method and Description |
|---|---|
Instance |
IteratorPipe.nextInstance() |
Instance |
TokenSequenceRemoveStopwords.pipe(Instance carrier) |
Instance |
TokenSequenceRemoveNonAlpha.pipe(Instance carrier) |
Instance |
TokenSequenceParseFeatureString.pipe(Instance carrier) |
Instance |
TokenSequenceNGrams.pipe(Instance carrier) |
Instance |
TokenSequenceMatchDataAndTarget.pipe(Instance carrier) |
Instance |
TokenSequenceLowercase.pipe(Instance carrier) |
Instance |
TokenSequence2TokenIterator.pipe(Instance carrier) |
Instance |
TokenSequence2FeatureVectorSequence.pipe(Instance carrier) |
Instance |
TokenSequence2FeatureSequenceWithBigrams.pipe(Instance carrier) |
Instance |
TokenSequence2FeatureSequence.pipe(Instance carrier) |
Instance |
Token2FeatureVector.pipe(Instance carrier) |
Instance |
TargetRememberLastLabel.pipe(Instance carrier) |
Instance |
Target2LabelSequence.pipe(Instance carrier) |
Instance |
Target2Label.pipe(Instance carrier) |
Instance |
Target2FeatureSequence.pipe(Instance carrier) |
Instance |
StringAddNewLineDelimiter.pipe(Instance carrier) |
Instance |
SourceLocation2TokenSequence.pipe(Instance carrier) |
Instance |
SimpleTaggerSentence2TokenSequence.pipe(Instance carrier)
Takes an instance with data of type String or String[][] and creates
an Instance of type TokenSequence.
|
Instance |
SerialPipes.pipe(Instance carrier) |
Instance |
SelectiveSGML2TokenSequence.pipe(Instance carrier) |
Instance |
SaveDataInSource.pipe(Instance carrier) |
Instance |
SGML2TokenSequence.pipe(Instance carrier) |
Instance |
PrintTokenSequenceFeatures.pipe(Instance carrier) |
Instance |
PrintInputAndTarget.pipe(Instance carrier) |
Instance |
PrintInput.pipe(Instance carrier) |
abstract Instance |
Pipe.pipe(Instance carrier)
Process an Instance.
|
Instance |
ParallelPipes.pipe(Instance carrier) |
Instance |
Noop.pipe(Instance carrier) |
Instance |
MakeAmpersandXMLFriendly.pipe(Instance carrier) |
Instance |
LineGroupString2TokenSequence.pipe(Instance carrier) |
Instance |
IteratingPipe.pipe(Instance carrier) |
Instance |
InstanceListTrimFeaturesByCount.pipe(Instance carrier) |
Instance |
Input2CharSequence.pipe(Instance carrier) |
Instance |
Filename2CharSequence.pipe(Instance carrier) |
Instance |
FeatureVectorConjunctions.pipe(Instance carrier) |
Instance |
FeatureValueString2FeatureVector.pipe(Instance carrier) |
Instance |
FeatureSequence2FeatureVector.pipe(Instance carrier) |
Instance |
FeatureSequence2AugmentableFeatureVector.pipe(Instance carrier) |
Instance |
Directory2FileIterator.pipe(Instance carrier) |
Instance |
Csv2FeatureVector.pipe(Instance carrier)
Convert the data in the given Instance from a CharSequence
of sparse feature-value pairs to a FeatureVector
|
Instance |
Csv2Array.pipe(Instance carrier)
Convert the data in an
Instance from a CharSequence
of comma-separated-values to an array, where each index is the
feature name. |
Instance |
Classification2ConfidencePredictingFeatureVector.pipe(Instance carrier) |
Instance |
CharSubsequence.pipe(Instance carrier) |
Instance |
CharSequenceReplace.pipe(Instance carrier) |
Instance |
CharSequenceArray2TokenSequence.pipe(Instance carrier) |
Instance |
CharSequence2TokenSequence.pipe(Instance carrier) |
Instance |
CharSequence2CharNGrams.pipe(Instance carrier) |
Instance |
AugmentableFeatureVectorLogScale.pipe(Instance carrier) |
Instance |
AugmentableFeatureVectorAddConjunctions.pipe(Instance carrier) |
Instance |
Array2FeatureVector.pipe(Instance carrier)
Convert the data in an
Instance from an array to a
FeatureVector leaving other fields unchanged. |
Instance |
AddClassifierTokenPredictions.pipe(Instance carrier)
Add the token classifier's predictions as features to the instance.
|
Instance |
SerialPipes.pipe(Instance carrier,
int startingIndex) |
Instance |
SerialPipes.pipe(Instance carrier,
int startingIndex,
boolean growAlphabet) |
Instance |
Pipe.pipe(Object data,
Object target,
Object name,
Object source,
Instance parent,
PropertyList properties)
Create and process an Instance.
|
| Modifier and Type | Method and Description |
|---|---|
Classification |
AddClassifierTokenPredictions.TokenClassifiers.classify(Instance instance) |
Classification |
AddClassifierTokenPredictions.TokenClassifiers.classify(Instance instance,
boolean useOutOfFold) |
static InstanceList |
AddClassifierTokenPredictions.convert(Instance inst,
Noop alphabetsPipe) |
static PipeOutputAccumulator |
IteratingPipe.iteratePipe(Pipe iteratedPipe,
PipeOutputAccumulator accumulator,
Instance carrier) |
Instance |
TokenSequenceRemoveStopwords.pipe(Instance carrier) |
Instance |
TokenSequenceRemoveNonAlpha.pipe(Instance carrier) |
Instance |
TokenSequenceParseFeatureString.pipe(Instance carrier) |
Instance |
TokenSequenceNGrams.pipe(Instance carrier) |
Instance |
TokenSequenceMatchDataAndTarget.pipe(Instance carrier) |
Instance |
TokenSequenceLowercase.pipe(Instance carrier) |
Instance |
TokenSequence2TokenIterator.pipe(Instance carrier) |
Instance |
TokenSequence2FeatureVectorSequence.pipe(Instance carrier) |
Instance |
TokenSequence2FeatureSequenceWithBigrams.pipe(Instance carrier) |
Instance |
TokenSequence2FeatureSequence.pipe(Instance carrier) |
Instance |
Token2FeatureVector.pipe(Instance carrier) |
Instance |
TargetRememberLastLabel.pipe(Instance carrier) |
Instance |
Target2LabelSequence.pipe(Instance carrier) |
Instance |
Target2Label.pipe(Instance carrier) |
Instance |
Target2FeatureSequence.pipe(Instance carrier) |
Instance |
StringAddNewLineDelimiter.pipe(Instance carrier) |
Instance |
SourceLocation2TokenSequence.pipe(Instance carrier) |
Instance |
SimpleTaggerSentence2TokenSequence.pipe(Instance carrier)
Takes an instance with data of type String or String[][] and creates
an Instance of type TokenSequence.
|
Instance |
SerialPipes.pipe(Instance carrier) |
Instance |
SelectiveSGML2TokenSequence.pipe(Instance carrier) |
Instance |
SaveDataInSource.pipe(Instance carrier) |
Instance |
SGML2TokenSequence.pipe(Instance carrier) |
Instance |
PrintTokenSequenceFeatures.pipe(Instance carrier) |
Instance |
PrintInputAndTarget.pipe(Instance carrier) |
Instance |
PrintInput.pipe(Instance carrier) |
abstract Instance |
Pipe.pipe(Instance carrier)
Process an Instance.
|
Instance |
ParallelPipes.pipe(Instance carrier) |
Instance |
Noop.pipe(Instance carrier) |
Instance |
MakeAmpersandXMLFriendly.pipe(Instance carrier) |
Instance |
LineGroupString2TokenSequence.pipe(Instance carrier) |
Instance |
IteratingPipe.pipe(Instance carrier) |
Instance |
InstanceListTrimFeaturesByCount.pipe(Instance carrier) |
Instance |
Input2CharSequence.pipe(Instance carrier) |
Instance |
Filename2CharSequence.pipe(Instance carrier) |
Instance |
FeatureVectorConjunctions.pipe(Instance carrier) |
Instance |
FeatureValueString2FeatureVector.pipe(Instance carrier) |
Instance |
FeatureSequence2FeatureVector.pipe(Instance carrier) |
Instance |
FeatureSequence2AugmentableFeatureVector.pipe(Instance carrier) |
Instance |
Directory2FileIterator.pipe(Instance carrier) |
Instance |
Csv2FeatureVector.pipe(Instance carrier)
Convert the data in the given Instance from a CharSequence
of sparse feature-value pairs to a FeatureVector
|
Instance |
Csv2Array.pipe(Instance carrier)
Convert the data in an
Instance from a CharSequence
of comma-separated-values to an array, where each index is the
feature name. |
Instance |
Classification2ConfidencePredictingFeatureVector.pipe(Instance carrier) |
Instance |
CharSubsequence.pipe(Instance carrier) |
Instance |
CharSequenceReplace.pipe(Instance carrier) |
Instance |
CharSequenceArray2TokenSequence.pipe(Instance carrier) |
Instance |
CharSequence2TokenSequence.pipe(Instance carrier) |
Instance |
CharSequence2CharNGrams.pipe(Instance carrier) |
Instance |
AugmentableFeatureVectorLogScale.pipe(Instance carrier) |
Instance |
AugmentableFeatureVectorAddConjunctions.pipe(Instance carrier) |
Instance |
Array2FeatureVector.pipe(Instance carrier)
Convert the data in an
Instance from an array to a
FeatureVector leaving other fields unchanged. |
Instance |
AddClassifierTokenPredictions.pipe(Instance carrier)
Add the token classifier's predictions as features to the instance.
|
Instance |
SerialPipes.pipe(Instance carrier,
int startingIndex) |
Instance |
SerialPipes.pipe(Instance carrier,
int startingIndex,
boolean growAlphabet) |
Instance |
Pipe.pipe(Object data,
Object target,
Object name,
Object source,
Instance parent,
PropertyList properties)
Create and process an Instance.
|
void |
PipeOutputArrayList.pipeOutputAccumulate(Instance carrier,
Pipe iteratedPipe) |
void |
PipeOutputAccumulator.pipeOutputAccumulate(Instance carrier,
Pipe subPipe) |
| Modifier and Type | Field and Description |
|---|---|
protected Instance |
AbstractPipeInputIterator.parentInstance |
| Modifier and Type | Method and Description |
|---|---|
Instance |
SimpleFileIterator.nextInstance() |
Instance |
SegmentIterator.nextInstance() |
Instance |
RandomTokenSequenceIterator.nextInstance() |
Instance |
RandomFeatureVectorIterator.nextInstance() |
Instance |
PipeInputIterator.nextInstance() |
Instance |
PipeExtendedIterator.nextInstance() |
Instance |
PatternMatchIterator.nextInstance() |
Instance |
ParenGroupIterator.nextInstance() |
Instance |
NestedIterator.nextInstance() |
Instance |
LineIterator.nextInstance() |
Instance |
LineGroupIterator.nextInstance() |
Instance |
InstanceListIterator.nextInstance() |
Instance |
FileUriIterator.nextInstance() |
Instance |
FileListIterator.nextInstance() |
Instance |
FileIterator.nextInstance() |
Instance |
CsvIterator.nextInstance() |
Instance |
ArrayIterator.nextInstance() |
Instance |
ArrayDataAndTargetIterator.nextInstance() |
abstract Instance |
AbstractPipeInputIterator.nextInstance() |
| Modifier and Type | Method and Description |
|---|---|
void |
PipeInputIterator.setParentInstance(Instance parent)
To be called once before iterator starts.
|
void |
AbstractPipeInputIterator.setParentInstance(Instance carrier) |
| Constructor and Description |
|---|
SegmentIterator(Instance instance,
Object[] startTags,
Object[] inTags,
Sequence prediction)
Iterate over segments in one instance.
|
SegmentIterator(Transducer model,
Instance instance,
Object[] segmentStartTags,
Object[] segmentContinueTags)
|
| Modifier and Type | Method and Description |
|---|---|
Instance |
TestSGML2TokenSequence.Array2ArrayIterator.pipe(Instance carrier) |
Instance |
TestInstancePipe.Array2ArrayIterator.pipe(Instance carrier) |
| Modifier and Type | Method and Description |
|---|---|
Instance |
TestSGML2TokenSequence.Array2ArrayIterator.pipe(Instance carrier) |
Instance |
TestInstancePipe.Array2ArrayIterator.pipe(Instance carrier) |
| Modifier and Type | Method and Description |
|---|---|
Instance |
TrieLexiconMembership.pipe(Instance carrier) |
Instance |
TokenTextNGrams.pipe(Instance carrier) |
Instance |
TokenTextCharSuffix.pipe(Instance carrier) |
Instance |
TokenTextCharPrefix.pipe(Instance carrier) |
Instance |
TokenTextCharNGrams.pipe(Instance carrier) |
Instance |
TokenText.pipe(Instance carrier) |
Instance |
Target2BIOFormat.pipe(Instance carrier) |
Instance |
SequencePrintingPipe.pipe(Instance carrier) |
Instance |
RegexMatches.pipe(Instance carrier) |
Instance |
OffsetPropertyConjunctions.pipe(Instance carrier) |
Instance |
OffsetFeatureConjunction.pipe(Instance carrier) |
Instance |
OffsetConjunctions.pipe(Instance carrier) |
Instance |
LexiconMembership.pipe(Instance carrier) |
Instance |
FeaturesOfFirstMention.pipe(Instance carrier) |
Instance |
FeaturesInWindow.pipe(Instance carrier) |
Instance |
CountMatchesMatching.pipe(Instance carrier) |
Instance |
CountMatchesAlignedWithOffsets.pipe(Instance carrier) |
Instance |
CountMatches.pipe(Instance carrier) |
| Modifier and Type | Method and Description |
|---|---|
Instance |
TrieLexiconMembership.pipe(Instance carrier) |
Instance |
TokenTextNGrams.pipe(Instance carrier) |
Instance |
TokenTextCharSuffix.pipe(Instance carrier) |
Instance |
TokenTextCharPrefix.pipe(Instance carrier) |
Instance |
TokenTextCharNGrams.pipe(Instance carrier) |
Instance |
TokenText.pipe(Instance carrier) |
Instance |
Target2BIOFormat.pipe(Instance carrier) |
Instance |
SequencePrintingPipe.pipe(Instance carrier) |
Instance |
RegexMatches.pipe(Instance carrier) |
Instance |
OffsetPropertyConjunctions.pipe(Instance carrier) |
Instance |
OffsetFeatureConjunction.pipe(Instance carrier) |
Instance |
OffsetConjunctions.pipe(Instance carrier) |
Instance |
LexiconMembership.pipe(Instance carrier) |
Instance |
FeaturesOfFirstMention.pipe(Instance carrier) |
Instance |
FeaturesInWindow.pipe(Instance carrier) |
Instance |
CountMatchesMatching.pipe(Instance carrier) |
Instance |
CountMatchesAlignedWithOffsets.pipe(Instance carrier) |
Instance |
CountMatches.pipe(Instance carrier) |
| Modifier and Type | Method and Description |
|---|---|
Instance |
PagedInstanceList.getInstance(int index)
Returns the
Instance at the specified index. |
Instance |
InstanceList.getInstance(int index)
Returns the
Instance at the specified index. |
Instance |
Instance.getPipedCopy(Pipe p) |
Instance |
InstanceList.Iterator.nextInstance() |
Instance |
Instance.Iterator.nextInstance() |
Instance |
Instance.shallowCopy() |
| Modifier and Type | Method and Description |
|---|---|
boolean |
PagedInstanceList.add(Instance instance)
Appends the instance to this list.
|
boolean |
InstanceList.add(Instance instance)
Appends the instance to this list.
|
boolean |
InstanceList.add(Instance instance,
double instanceWeight)
Appends the instance to this list, assigning it the specified weight.
|
void |
TokenSequence.pipeOutputAccumulate(Instance carrier,
Pipe iteratedPipe) |
void |
InstanceList.pipeOutputAccumulate(Instance carrier,
Pipe iteratedPipe) |
void |
PagedInstanceList.setInstance(int index,
Instance instance)
Replaces the
Instance at position
index with a new one. |
void |
InstanceList.setInstance(int index,
Instance instance)
Replaces the
Instance at position index
with a new one. |
| Modifier and Type | Method and Description |
|---|---|
Instance |
MentionPairIterator.nextInstance() |
Instance |
TokenFeaturesMentionPair.pipe(Instance carrier) |
Instance |
PartOfSpeechMentionPair.pipe(Instance carrier) |
Instance |
NullAntecedentFeatureExtractor.pipe(Instance carrier) |
Instance |
ModifierWordFeatures.pipe(Instance carrier) |
Instance |
MentionPairSubstring.pipe(Instance carrier) |
Instance |
MentionPairSentenceDistance.pipe(Instance carrier) |
Instance |
MentionPairNPDistance.pipe(Instance carrier) |
Instance |
MentionPairIdentical.pipe(Instance carrier) |
Instance |
MentionPairHeadIdentical.pipe(Instance carrier) |
Instance |
MentionPairAntecedentPosition.pipe(Instance carrier) |
Instance |
MentionPair2FeatureVectorFilter.pipe(Instance carrier) |
Instance |
MentionPair2FeatureVector.pipe(Instance carrier) |
Instance |
LinearDistanceMentionPair.pipe(Instance carrier) |
Instance |
HobbsDistanceMentionPair.pipe(Instance carrier) |
Instance |
GenderMentionPair.pipe(Instance carrier) |
Instance |
AffixOfMentionPair.pipe(Instance carrier) |
Instance |
AcronymOf.pipe(Instance carrier) |
Instance |
AceTypeFeature.pipe(Instance carrier) |
| Modifier and Type | Method and Description |
|---|---|
Instance |
TokenFeaturesMentionPair.pipe(Instance carrier) |
Instance |
PartOfSpeechMentionPair.pipe(Instance carrier) |
Instance |
NullAntecedentFeatureExtractor.pipe(Instance carrier) |
Instance |
ModifierWordFeatures.pipe(Instance carrier) |
Instance |
MentionPairSubstring.pipe(Instance carrier) |
Instance |
MentionPairSentenceDistance.pipe(Instance carrier) |
Instance |
MentionPairNPDistance.pipe(Instance carrier) |
Instance |
MentionPairIdentical.pipe(Instance carrier) |
Instance |
MentionPairHeadIdentical.pipe(Instance carrier) |
Instance |
MentionPairAntecedentPosition.pipe(Instance carrier) |
Instance |
MentionPair2FeatureVectorFilter.pipe(Instance carrier) |
Instance |
MentionPair2FeatureVector.pipe(Instance carrier) |
Instance |
LinearDistanceMentionPair.pipe(Instance carrier) |
Instance |
HobbsDistanceMentionPair.pipe(Instance carrier) |
Instance |
GenderMentionPair.pipe(Instance carrier) |
Instance |
AffixOfMentionPair.pipe(Instance carrier) |
Instance |
AcronymOf.pipe(Instance carrier) |
Instance |
AceTypeFeature.pipe(Instance carrier) |
| Modifier and Type | Method and Description |
|---|---|
Instance |
LineGroupIterator2.nextInstance() |
Instance |
SGML2FieldsPipe.pipe(Instance carrier) |
| Modifier and Type | Method and Description |
|---|---|
protected void |
ClusterLearner.constructEdges(MappedGraph graph,
Instance pair,
Matrix2 lambdas) |
static void |
TUI.constructEdgesUsingTrainedClusterer(MappedGraph graph,
Instance instPair,
Matrix2 lambdas,
Pipe instancePipe) |
Instance |
SGML2FieldsPipe.pipe(Instance carrier) |
protected void |
CitationCluster.print(Instance instance) |
Object |
CitationCluster.updateCononicalObj(Instance instance) |
| Constructor and Description |
|---|
CitationCluster(Instance instance,
String refNoMeta,
String clusterNoMeta,
String[] startTags,
String[] endTags,
double[] tagWeight) |
| Modifier and Type | Method and Description |
|---|---|
Instance |
VenuePaperCluster2FeatureVector.pipe(Instance carrier) |
Instance |
VenueClusterPrediction.pipe(Instance carrier) |
Instance |
ThereExistsMatch.pipe(Instance carrier) |
Instance |
ThereExists.pipe(Instance carrier) |
Instance |
PaperClusterPrediction.pipe(Instance carrier) |
Instance |
NodeClusterPair2FeatureVector.pipe(Instance carrier) |
Instance |
NNegativeNodes.pipe(Instance carrier) |
Instance |
ForAll.pipe(Instance carrier) |
Instance |
FarthestSingleLink.pipe(Instance carrier) |
Instance |
ClusterSize.pipe(Instance carrier) |
Instance |
ClusterHomogeneity.pipe(Instance carrier) |
Instance |
ClosestSingleLink.pipe(Instance carrier) |
Instance |
AverageLink.pipe(Instance carrier) |
Instance |
AllLinks.pipe(Instance carrier) |
| Modifier and Type | Method and Description |
|---|---|
Instance |
VenuePaperCluster2FeatureVector.pipe(Instance carrier) |
Instance |
VenueClusterPrediction.pipe(Instance carrier) |
Instance |
ThereExistsMatch.pipe(Instance carrier) |
Instance |
ThereExists.pipe(Instance carrier) |
Instance |
PaperClusterPrediction.pipe(Instance carrier) |
Instance |
NodeClusterPair2FeatureVector.pipe(Instance carrier) |
Instance |
NNegativeNodes.pipe(Instance carrier) |
Instance |
ForAll.pipe(Instance carrier) |
Instance |
FarthestSingleLink.pipe(Instance carrier) |
Instance |
ClusterSize.pipe(Instance carrier) |
Instance |
ClusterHomogeneity.pipe(Instance carrier) |
Instance |
ClosestSingleLink.pipe(Instance carrier) |
Instance |
AverageLink.pipe(Instance carrier) |
Instance |
AllLinks.pipe(Instance carrier) |
| Modifier and Type | Method and Description |
|---|---|
Instance |
VenuePaperClusterIterator.nextInstance() |
Instance |
NodeClusterPairIterator.nextInstance() |
| Modifier and Type | Method and Description |
|---|---|
Instance |
PubCitIterator.nextInstance() |
Instance |
NodePairIterator.nextInstance() |
Instance |
YearsWithinFivePipe.pipe(Instance carrier) |
Instance |
YearPipe.pipe(Instance carrier) |
Instance |
VolumesMatchPipe.pipe(Instance carrier) |
Instance |
VenuePipe.pipe(Instance carrier) |
Instance |
VenueAcronymPipe.pipe(Instance carrier) |
Instance |
TitlePipe.pipe(Instance carrier) |
Instance |
TechPipe.pipe(Instance carrier) |
Instance |
StringDistances.pipe(Instance carrier) |
Instance |
SplitFieldStringDistancePipe.pipe(Instance carrier) |
Instance |
SGMLStringDistances.pipe(Instance carrier) |
Instance |
RegexPipe.pipe(Instance carrier) |
Instance |
PublisherPipe.pipe(Instance carrier) |
Instance |
PlainFieldPipe.pipe(Instance carrier) |
Instance |
PagesPipe.pipe(Instance carrier) |
Instance |
PageMatchPipe.pipe(Instance carrier) |
Instance |
NormalizationPipe.pipe(Instance carrier) |
Instance |
NodePairSaveSource.pipe(Instance carrier) |
Instance |
NodePair2FeatureVector.pipe(Instance carrier) |
Instance |
JournalPipe.pipe(Instance carrier) |
Instance |
InterFieldPipe.pipe(Instance carrier) |
Instance |
HeuristicPipe.pipe(Instance carrier) |
Instance |
GlobalPipeUnSeg.pipe(Instance carrier) |
Instance |
GlobalPipe.pipe(Instance carrier) |
Instance |
FuchunPipe.pipe(Instance carrier) |
Instance |
FieldStringDistancePipe.pipe(Instance carrier) |
Instance |
ExactFieldMatchPipe.pipe(Instance carrier) |
Instance |
DatePipe.pipe(Instance carrier) |
Instance |
BooktitlePipe.pipe(Instance carrier) |
Instance |
AuthorPipe.pipe(Instance carrier) |
Instance |
AuthorLastNameEqual.pipe(Instance carrier) |
| Modifier and Type | Method and Description |
|---|---|
void |
CorefClusterAdv.constructEdgesUsingTrainedClusterer(salvo.jesus.graph.WeightedGraph graph,
Instance instPair,
HashMap alreadyAdded) |
void |
CorefClusterAdv.constructEdgesUsingTrainedClusterer(salvo.jesus.graph.WeightedGraph graph,
Instance instPair,
HashMap alreadyAdded,
Double edgeWeight) |
void |
CorefClusterAdv.constructEdgesUsingTrainedClusterer(salvo.jesus.graph.WeightedGraph graph,
Instance instPair,
HashMap alreadyAdded,
Double edgeWeight,
MaxEnt classifier) |
static void |
CorefCluster2.constructEdgesUsingTrainedClusterer(salvo.jesus.graph.WeightedGraph graph,
Instance instPair,
HashMap alreadyAdded,
MaxEnt classifier) |
static void |
CorefCluster.constructEdgesUsingTrainedClusterer(salvo.jesus.graph.WeightedGraph graph,
Instance instPair,
HashMap alreadyAdded,
MaxEnt classifier) |
double |
ComputeUpperBound1.PairSimilarity(Sequence sequence1,
Sequence sequence2,
Instance instance1,
Instance instance2) |
Instance |
YearsWithinFivePipe.pipe(Instance carrier) |
Instance |
YearPipe.pipe(Instance carrier) |
Instance |
VolumesMatchPipe.pipe(Instance carrier) |
Instance |
VenuePipe.pipe(Instance carrier) |
Instance |
VenueAcronymPipe.pipe(Instance carrier) |
Instance |
TitlePipe.pipe(Instance carrier) |
Instance |
TechPipe.pipe(Instance carrier) |
Instance |
StringDistances.pipe(Instance carrier) |
Instance |
SplitFieldStringDistancePipe.pipe(Instance carrier) |
Instance |
SGMLStringDistances.pipe(Instance carrier) |
Instance |
RegexPipe.pipe(Instance carrier) |
Instance |
PublisherPipe.pipe(Instance carrier) |
Instance |
PlainFieldPipe.pipe(Instance carrier) |
Instance |
PagesPipe.pipe(Instance carrier) |
Instance |
PageMatchPipe.pipe(Instance carrier) |
Instance |
NormalizationPipe.pipe(Instance carrier) |
Instance |
NodePairSaveSource.pipe(Instance carrier) |
Instance |
NodePair2FeatureVector.pipe(Instance carrier) |
Instance |
JournalPipe.pipe(Instance carrier) |
Instance |
InterFieldPipe.pipe(Instance carrier) |
Instance |
HeuristicPipe.pipe(Instance carrier) |
Instance |
GlobalPipeUnSeg.pipe(Instance carrier) |
Instance |
GlobalPipe.pipe(Instance carrier) |
Instance |
FuchunPipe.pipe(Instance carrier) |
Instance |
FieldStringDistancePipe.pipe(Instance carrier) |
Instance |
ExactFieldMatchPipe.pipe(Instance carrier) |
Instance |
DatePipe.pipe(Instance carrier) |
Instance |
BooktitlePipe.pipe(Instance carrier) |
Instance |
AuthorPipe.pipe(Instance carrier) |
Instance |
AuthorLastNameEqual.pipe(Instance carrier) |
| Modifier and Type | Method and Description |
|---|---|
Instance |
TUI_CorefIE.ClusterListIterator.nextInstance() |
Instance |
TUI_CorefIE.WordAppearsInAnyClusterPipe.pipe(Instance carrier) |
Instance |
TUI_CorefIE.WordOftenAppearsAsPipe.pipe(Instance carrier) |
Instance |
TUI_CorefIE.NegativeClusterFeaturePipe.pipe(Instance carrier) |
Instance |
TUI_CorefIE.NumAppearancesInClusterPipe.pipe(Instance carrier) |
Instance |
TUI_CorefIE.BogusClusterPipe.pipe(Instance carrier) |
Instance |
POSFeaturesPipe.pipe(Instance carrier) |
| Modifier and Type | Method and Description |
|---|---|
InstanceList |
TUI_CorefIE.AllClusterSegmentation.getCluster(Instance inst) |
TUI_CorefIE.Segmentation |
TUI_CorefIE.AllClusterSegmentation.getSegmentation(Instance inst) |
double |
IEInterface.InstanceAccuracy(Sequence viterbiSequence,
Instance instance) |
double |
IEInterface.InstanceAccuracy(Sequence viterbiSequence,
Sequence targetSequence,
Instance instance) |
Instance |
TUI_CorefIE.WordAppearsInAnyClusterPipe.pipe(Instance carrier) |
Instance |
TUI_CorefIE.WordOftenAppearsAsPipe.pipe(Instance carrier) |
Instance |
TUI_CorefIE.NegativeClusterFeaturePipe.pipe(Instance carrier) |
Instance |
TUI_CorefIE.NumAppearancesInClusterPipe.pipe(Instance carrier) |
Instance |
TUI_CorefIE.BogusClusterPipe.pipe(Instance carrier) |
Instance |
POSFeaturesPipe.pipe(Instance carrier) |
String |
IEInterface3.viterbiCRFInstance_NBest(Instance instance,
boolean sgml) |
String |
IEInterface.viterbiCRFInstance_NBest(Instance instance,
boolean sgml,
int N) |
String |
IEInterface3.viterbiCRFInstance(Instance instance,
boolean sgml) |
String |
IEInterface.viterbiCRFInstance(Instance instance,
boolean sgml) |
| Modifier and Type | Method and Description |
|---|---|
Instance |
ConllNer2003Sentence2TokenSequence.pipe(Instance carrier) |
| Modifier and Type | Method and Description |
|---|---|
Instance |
ConllNer2003Sentence2TokenSequence.pipe(Instance carrier) |
| Modifier and Type | Method and Description |
|---|---|
Instance |
TokenSequenceDocHeader.pipe(Instance carrier) |
Instance |
ConllNer2003Sentence2TokenSequence.pipe(Instance carrier) |
| Modifier and Type | Method and Description |
|---|---|
Instance |
TokenSequenceDocHeader.pipe(Instance carrier) |
Instance |
ConllNer2003Sentence2TokenSequence.pipe(Instance carrier) |
| Modifier and Type | Method and Description |
|---|---|
Instance |
LongRegexMatches.pipe(Instance carrier) |
Instance |
ListMember.pipe(Instance carrier) |
Instance |
LengthBins.pipe(Instance carrier) |
Instance |
FeatureWindow.pipe(Instance carrier) |
| Modifier and Type | Method and Description |
|---|---|
Instance |
LongRegexMatches.pipe(Instance carrier) |
Instance |
ListMember.pipe(Instance carrier) |
Instance |
LengthBins.pipe(Instance carrier) |
Instance |
FeatureWindow.pipe(Instance carrier) |
| Modifier and Type | Method and Description |
|---|---|
Instance |
EnronMessage2TokenSequence.pipe(Instance carrier) |
| Modifier and Type | Method and Description |
|---|---|
Instance |
EnronMessage2TokenSequence.pipe(Instance carrier) |
Copyright © 2019 JULIE Lab, Germany. All rights reserved.