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Strings.
Strings.
Strings.
BalancedWinnowTrainer
Transducer.
Segment extracted by a Transducer by performing a "constrained lattice"
calculation.Segments produced by a Transducer.ogc such that nodes that resolve to the
same paper are forced to have the same venue.
ogc such that nodes with venues from
different venue clusters will be in different clusters.
- constructEdges(MappedGraph, Instance, Matrix2) -
Method in class edu.umass.cs.mallet.projects.seg_plus_coref.clustering.ClusterLearner
-
- constructEdgesFromPseudoEdges(WeightedGraph, CorefClusterAdv.PseudoEdge, HashMap) -
Method in class edu.umass.cs.mallet.projects.seg_plus_coref.coreference.CorefClusterAdv
-
- constructEdgesUsingTrainedClusterer(MappedGraph, Instance, Matrix2, Pipe) -
Static method in class edu.umass.cs.mallet.projects.seg_plus_coref.clustering.TUI
-
- constructEdgesUsingTrainedClusterer(WeightedGraph, Instance, HashMap, MaxEnt) -
Static method in class edu.umass.cs.mallet.projects.seg_plus_coref.coreference.CorefCluster
-
- constructEdgesUsingTrainedClusterer(WeightedGraph, Instance, HashMap, MaxEnt) -
Static method in class edu.umass.cs.mallet.projects.seg_plus_coref.coreference.CorefCluster2
-
- constructEdgesUsingTrainedClusterer(WeightedGraph, Instance, HashMap) -
Method in class edu.umass.cs.mallet.projects.seg_plus_coref.coreference.CorefClusterAdv
-
- constructEdgesUsingTrainedClusterer(WeightedGraph, Instance, HashMap, Double) -
Method in class edu.umass.cs.mallet.projects.seg_plus_coref.coreference.CorefClusterAdv
-
- constructEdgesUsingTrainedClusterer(WeightedGraph, Instance, HashMap, Double, MaxEnt) -
Method in class edu.umass.cs.mallet.projects.seg_plus_coref.coreference.CorefClusterAdv
-
- constructLabeledSpans(LabelAlphabet, Object, Label, Tokenization, Sequence) -
Method in class edu.umass.cs.mallet.base.extract.BIOTokenizationFilter
-
- constructLabeledSpans(LabelAlphabet, Object, Label, Tokenization, Sequence) -
Method in class edu.umass.cs.mallet.base.extract.ConfidenceTokenizationFilter
-
- constructLabeledSpans(LabelAlphabet, Object, Label, Tokenization, Sequence) -
Method in class edu.umass.cs.mallet.base.extract.DefaultTokenizationFilter
-
- constructLabeledSpans(LabelAlphabet, Object, Label, Tokenization, Sequence) -
Method in class edu.umass.cs.mallet.base.extract.HierarchicalTokenizationFilter
-
- constructLabeledSpans(LabelAlphabet, Object, Label, Tokenization, Sequence) -
Method in interface edu.umass.cs.mallet.base.extract.TokenizationFilter
- Converts a the sequence of labels into a set of labeled spans.
- constructOptimalEdgesUsingNBest(List, int) -
Method in class edu.umass.cs.mallet.projects.seg_plus_coref.coreference.CorefClusterAdv
-
- constructPhrases(Element, MalletPreTerm, MalletSentence, String) -
Method in class edu.umass.cs.mallet.projects.seg_plus_coref.anaphora.MalletDocumentElement
-
- constructPreTerms(Element, MalletSentence) -
Method in class edu.umass.cs.mallet.projects.seg_plus_coref.anaphora.MalletDocumentElement
-
- contains(Object) -
Method in class edu.umass.cs.mallet.base.types.Alphabet
-
- contains(Object) -
Method in class edu.umass.cs.mallet.base.types.DenseFeatureVector
-
- contains(Object) -
Method in class edu.umass.cs.mallet.base.types.FeatureSelection
-
- contains(int) -
Method in class edu.umass.cs.mallet.base.types.FeatureSelection
-
- contains(Object) -
Method in class edu.umass.cs.mallet.base.types.FeatureVector
-
- contains(QueueElement) -
Method in class edu.umass.cs.mallet.base.util.search.MinHeap
-
- contains(QueueElement) -
Method in interface edu.umass.cs.mallet.base.util.search.PriorityQueue
- Does the queue contain an element?
- contentsAsCharSequence(Reader) -
Static method in class edu.umass.cs.mallet.base.util.IoUtils
-
- contentsAsString(File) -
Static method in class edu.umass.cs.mallet.base.util.IoUtils
-
- convert(InstanceList, Noop) -
Static method in class edu.umass.cs.mallet.base.pipe.AddClassifierTokenPredictions
- Converts each instance containing a FeatureVectorSequence to multiple instances,
each containing an AugmentableFeatureVector as data.
- convert(Instance, Noop) -
Static method in class edu.umass.cs.mallet.base.pipe.AddClassifierTokenPredictions
-
- convertToMentions(Vector) -
Method in class edu.umass.cs.mallet.projects.seg_plus_coref.anaphora.MentionPairIterator.DocumentMentionPairIterator
-
- copyGraph(WeightedGraph) -
Method in class edu.umass.cs.mallet.projects.seg_plus_coref.coreference.CorefClusterAdv
-
- corefFields -
Static variable in class edu.umass.cs.mallet.projects.seg_plus_coref.coreference.Citation
-
- corr(Univariate, Univariate) -
Static method in class edu.umass.cs.mallet.base.util.StatFunctions
-
- correct() -
Method in class edu.umass.cs.mallet.base.fst.Segment
-
- correct() -
Method in class edu.umass.cs.mallet.base.fst.confidence.ConfidenceEvaluator.EntityConfidence
-
- correct() -
Method in class edu.umass.cs.mallet.base.fst.confidence.InstanceWithConfidence
-
- correct() -
Method in class edu.umass.cs.mallet.base.fst.confidence.PipedInstanceWithConfidence
-
- correctLeastConfidentSegments(InstanceList, Object[], Object[]) -
Method in class edu.umass.cs.mallet.base.fst.confidence.ConstrainedViterbiTransducerCorrector
-
- correctLeastConfidentSegments(InstanceList, Object[], Object[], boolean) -
Method in class edu.umass.cs.mallet.base.fst.confidence.ConstrainedViterbiTransducerCorrector
- Returns an ArrayList of corrected Sequences.
- correctLeastConfidentSegments(InstanceList, Object[], Object[]) -
Method in class edu.umass.cs.mallet.base.fst.confidence.IsolatedSegmentTransducerCorrector
-
- correctLeastConfidentSegments(InstanceList, Object[], Object[]) -
Method in interface edu.umass.cs.mallet.base.fst.confidence.TransducerCorrector
-
- correlation() -
Method in class edu.umass.cs.mallet.base.fst.confidence.ConfidenceEvaluator
- Calculate pearson's R for the corellation between confidence and
correct, where 1 = correct and -1 = incorrect
- cosh(double) -
Static method in class edu.umass.cs.mallet.base.util.Maths
-
- cost -
Variable in class edu.umass.cs.mallet.base.types.SequencePairAlignment
-
- cost() -
Method in class edu.umass.cs.mallet.base.util.search.SearchNode.NextNodeIterator
- The cost associated to the transition from the previous
state to this state.
- cost() -
Method in class edu.umass.cs.mallet.base.util.search.SearchState.NextStateIterator
- The cost of the transition to the current state.
- costNBest -
Variable in class edu.umass.cs.mallet.base.types.SequencePair
-
- costNBest() -
Method in class edu.umass.cs.mallet.base.types.SequencePair
-
- costs -
Variable in class edu.umass.cs.mallet.base.fst.CRF4.TransitionIterator
-
- count(int[], int) -
Static method in class edu.umass.cs.mallet.base.util.ArrayUtils
- Returns the number of times a value occurs in a given array.
- count(String, char) -
Static method in class edu.umass.cs.mallet.base.util.Strings
-
- cov(Univariate, Univariate) -
Static method in class edu.umass.cs.mallet.base.util.StatFunctions
-
- createAccuracyArray() -
Method in class edu.umass.cs.mallet.base.classify.evaluate.AccuracyCoverage
- Creates array of accuracy values for coverage
at each step as defined by numBuckets.
- createArrayList(Object[]) -
Static method in class edu.umass.cs.mallet.base.util.ArrayListUtils
-
- createFromRegex(Alphabet, Pattern) -
Static method in class edu.umass.cs.mallet.base.types.FeatureSelection
- Creates a FeatureSelection that includes only those features whose names match a given regex.
- createGainRatio(InstanceList) -
Static method in class edu.umass.cs.mallet.base.types.GainRatio
- Constructs a GainRatio object.
- createGainRatio(InstanceList, int[], int) -
Static method in class edu.umass.cs.mallet.base.types.GainRatio
- Constructs a GainRatio object
- createGraph(InstanceList, List) -
Method in class edu.umass.cs.mallet.projects.seg_plus_coref.coreference.CorefClusterAdv
-
- createGraph(InstanceList, List, WeightedGraph) -
Method in class edu.umass.cs.mallet.projects.seg_plus_coref.coreference.CorefClusterAdv
-
- createGraph(InstanceList, List, WeightedGraph, MaxEnt) -
Method in class edu.umass.cs.mallet.projects.seg_plus_coref.coreference.CorefClusterAdv
-
- createNodesFromFiles(String[], IEInterface, String) -
Method in class edu.umass.cs.mallet.projects.seg_plus_coref.condclust.tui.PairwiseClustererTUI
- Read citation files and create nodes
- createPseudoEdges(InstanceList, Map) -
Method in class edu.umass.cs.mallet.projects.seg_plus_coref.coreference.CorefClusterAdv
-
- createPseudoVertices(InstanceList, List, HashMap) -
Method in class edu.umass.cs.mallet.projects.seg_plus_coref.coreference.CorefClusterAdv
-
- createSpan(Tokenization, int, int) -
Method in class edu.umass.cs.mallet.base.extract.BIOTokenizationFilter
-
- crf -
Variable in class edu.umass.cs.mallet.projects.seg_plus_coref.ie.IEInterface
-
- crossValidationIterator(int, int) -
Method in class edu.umass.cs.mallet.base.types.InstanceList
-
- crossValidationIterator(int) -
Method in class edu.umass.cs.mallet.base.types.InstanceList
-
- cumulativeAccuracy() -
Method in class edu.umass.cs.mallet.base.classify.evaluate.AccuracyCoverage
- Finds the "area under the acc/cov curve"
steps by one percentage point and calcs area
of trapezoid
- cumulativeEvaluate(File, String, int) -
Method in class edu.umass.cs.mallet.projects.seg_plus_coref.ie.IEInterface3
-
- cumulativeEvaluate_InstanceLevel(File, String, int) -
Method in class edu.umass.cs.mallet.projects.seg_plus_coref.ie.IEInterface
-
- cumulativeEvaluate_TokenLevel(File, String, int) -
Method in class edu.umass.cs.mallet.projects.seg_plus_coref.ie.IEInterface
-
e to priorrity.
Instance objects within an
InstanceList.Segment.
Segment.
Segment.
Segment.
Instance.
Instance.
Instance.
Segment.
Instance.
Instance.
Segment.
Sequence.
Instance.
Instance.
Sequence that ensures that every
Object in the sequence has the same class.Alphabet in which each element of the subset has an associated value.
FeaturesInWindow((namePrefix, leftBoundaryOffset, rightBoundaryOffset, null, true);
requiredSegment as indicated by
constrainedSequence
requiredSegment as indicated by
constrainedSequence
Instance at the specified index.
Alphabet mapping features of the data to
integers.
Instance in this list.
Instance at the specified index.
Instance at the specified index.
correctLeastConfidentSegments
ilist
Instance is passed,
which may be null.
Alphabet mapping target output labels to
integers.
FeatureVectors.
CrossValidationIterator allows iterating over pairs of
InstanceList, where each pair is split into training/testing
based on nfolds.Segments produced by a Transducer.e into the queue.
Sequence implementation where all of the
elements must be Labels.InstanceList, deserialized from file.
InstanceList, deserialized from
file.
Segment extracted by a Transducer using a MaxEnt classifier to classify segments
as "correct" or "incorrect." xxx needs some interface workSequence extracted by a Transducer using a MaxEnt classifier to classify Sequences
as "correct" or "incorrect." xxx needs some interface work.capacity.
FeatureVector.SparseVector whose entries (taken from the union of
those in the instances) are the expected values of those in the
InstanceList.
SparseVector whose entries (dense with the given
number of indices) are the expected values of those in the
InstanceList.
SparseVector whose entries (the given indices) are
the expected values of those in the InstanceList.
predOutput
PipeExtendedIterator that applies a Pipe to
the Instances returned by a given PipeExtendedIterator,
It is intended to encapsulate preprocessing that should not belong to the
input Pipe of a Classifier or Transducer.PipeExtendedIterator instance.
Instance from an array to a
FeatureVector leaving other fields unchanged.
Instance from a CharSequence
of comma-separated-values to an array, where each index is the
feature name.
Segment.Sequencess in this InstanceList by
confidence estimate.
Segments in this InstanceList by
confidence estimate.
Instance
null in all instances.
null in all instances.
Sequence segmented by a
Transducer, usually corresponding to some object extracted
from an input Sequence.Segments extracted by a Transducer
for some InstanceList.segmentStartTags[i] corresponds
to segmentContinueTags[i].
Segments for only one Instance.
Transduce is specified.
SGML2TokenSequence, except that only the tags
listed in allowedTags are converted to Labels.Sequence and a PropertyList, used when extracting
features from a Sequence in a pipe for confidence predictionFeatureVectorSequence.SimpleTaggerSentence2FeatureVectorSequence instance.
TokenSequence.SimpleTaggerSentence2TokenSequence instance.
SimpleTaggerSentence2TokenSequence instance
which includes tokens as features iff the supplied argument is true.
InstanceList of the same size, where the instances come from the
random sampling (with replacement) of this list using the instance weights.
InstanceList of the same size, where the instances come from the
random sampling (with replacement) of this list using the given weights.
InstanceList of the same size, where the instances come from the
random sampling (with replacement) of this list using the given weights.
InstanceList to file.
readString
Instance at position index
with a new one.
Instance at position
index with a new one.
train or trainWithFeatureInduction.
train or trainWithFeatureInduction.
mth element of this list, starting with the first.
mth element of this list,
starting with the first.
LabelSequence out of a TokenSequence that
is the target of an Instance.Segment
extracted by a Transducer.Segments produced by a Transducer.Sequence
extracted by a Transducer.Note that this is different from
TransducerConfidenceEstimator, which estimates the
confidence for a single Segment.weights according to errors
ilist.
trainWithFeatureInduction, but
allows some default options to be changed.
trainWithFeatureInduction, but
allows some default options to be changed.
SparseVector whose entries (taken from the union of
those in the instances) are the variance of those in the
InstanceList.
SparseVector whose entries (taken from the mean
argument) are the variance of those in the InstanceList.
WinnowTrainer
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