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String
s.
String
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String
s.
BalancedWinnowTrainer
Transducer
.
Segment
extracted by a Transducer
by performing a "constrained lattice"
calculation.Segment
s 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.
FeatureVector
s.
CrossValidationIterator
allows iterating over pairs of
InstanceList
, where each pair is split into training/testing
based on nfolds.Segment
s 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 Instance
s 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
.Sequences
s in this InstanceList
by
confidence estimate.
Segment
s 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
.Segment
s extracted by a Transducer
for some InstanceList
.segmentStartTags[i]
corresponds
to segmentContinueTags[i]
.
Segment
s for only one Instance
.
Transduce
is specified.
SGML2TokenSequence
, except that only the tags
listed in allowedTags
are converted to Label
s.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
.
m
th element of this list, starting with the first.
m
th 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
.Segment
s 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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