| Class and Description |
|---|
| Alphabet
A mapping between integers and objects where the mapping in each
direction is efficient.
|
| AugmentableFeatureVector |
| FeatureSelection |
| FeatureSelector |
| GainRatio
List of features along with their thresholds sorted in descending order of
the ratio of (1) information gained by splitting instances on the
feature at its associated threshold value, to (2) the split information.
|
| Instance
A machine learning "example" to be used in training, testing or
performance of various machine learning algorithms.
|
| InstanceList
A list of machine learning instances, typically used for training
or testing of a machine learning algorithm.
|
| LabelAlphabet
A mapping from arbitrary objects (usually String's) to integers
(and corresponding Label objects) and back.
|
| Labeling
A distribution over possible labels for an instance.
|
| LabelVector |
| Multinomial
A probability distribution over a set of features represented as a
FeatureVector. |
| Multinomial.Estimator
A hierarchy of classes used to produce estimates of probabilities, in
the form of a Multinomial, from counts associated with the elements
of an Alphabet.
|
| Multinomial.Logged
A Multinomial in which the values associated with each feature index fi is
Math.log(probability[fi]) instead of probability[fi].
|
| Class and Description |
|---|
| InstanceList
A list of machine learning instances, typically used for training
or testing of a machine learning algorithm.
|
| Class and Description |
|---|
| InstanceList
A list of machine learning instances, typically used for training
or testing of a machine learning algorithm.
|
| Metric |
| Class and Description |
|---|
| Alphabet
A mapping between integers and objects where the mapping in each
direction is efficient.
|
| ArrayListSequence |
| InstanceList
A list of machine learning instances, typically used for training
or testing of a machine learning algorithm.
|
| Label |
| LabelAlphabet
A mapping from arbitrary objects (usually String's) to integers
(and corresponding Label objects) and back.
|
| LabelSequence |
| PropertyHolder
Author: saunders Created Nov 15, 2005 Copyright (C) Univ.
|
| Sequence |
| Token
A representation of a piece of text, usually a single word, to
which we can attach properties.
|
| TokenSequence
A representation of a piece of text, usually a single word, to which we can attach properties.
|
| Class and Description |
|---|
| Instance
A machine learning "example" to be used in training, testing or
performance of various machine learning algorithms.
|
| Class and Description |
|---|
| Alphabet
A mapping between integers and objects where the mapping in each
direction is efficient.
|
| DenseVector |
| FeatureSelection |
| FeatureSequence
An implementation of
Sequence that ensures that every
Object in the sequence has the same class. |
| FeatureVector
A subset of an
Alphabet in which each element of the subset has an associated value. |
| FeatureVectorSequence |
| Instance
A machine learning "example" to be used in training, testing or
performance of various machine learning algorithms.
|
| InstanceList
A list of machine learning instances, typically used for training
or testing of a machine learning algorithm.
|
| LabelAlphabet
A mapping from arbitrary objects (usually String's) to integers
(and corresponding Label objects) and back.
|
| LabelVector |
| Matrix |
| Multinomial.Estimator
A hierarchy of classes used to produce estimates of probabilities, in
the form of a Multinomial, from counts associated with the elements
of an Alphabet.
|
| Sequence |
| SequencePair |
| SequencePairAlignment |
| SparseVector
A vector that allocates memory only for non-zero values.
|
| Class and Description |
|---|
| Instance
A machine learning "example" to be used in training, testing or
performance of various machine learning algorithms.
|
| InstanceList
A list of machine learning instances, typically used for training
or testing of a machine learning algorithm.
|
| Sequence |
| Class and Description |
|---|
| Instance
A machine learning "example" to be used in training, testing or
performance of various machine learning algorithms.
|
| Class and Description |
|---|
| Matrix |
| Class and Description |
|---|
| Matrix |
| Class and Description |
|---|
| Alphabet
A mapping between integers and objects where the mapping in each
direction is efficient.
|
| Instance
A machine learning "example" to be used in training, testing or
performance of various machine learning algorithms.
|
| InstanceList
A list of machine learning instances, typically used for training
or testing of a machine learning algorithm.
|
| LabelAlphabet
A mapping from arbitrary objects (usually String's) to integers
(and corresponding Label objects) and back.
|
| TokenSequence
A representation of a piece of text, usually a single word, to which we can attach properties.
|
| Class and Description |
|---|
| Alphabet
A mapping between integers and objects where the mapping in each
direction is efficient.
|
| Dirichlet |
| Instance
A machine learning "example" to be used in training, testing or
performance of various machine learning algorithms.
|
| InstanceList
A list of machine learning instances, typically used for training
or testing of a machine learning algorithm.
|
| LabelAlphabet
A mapping from arbitrary objects (usually String's) to integers
(and corresponding Label objects) and back.
|
| Sequence |
| Class and Description |
|---|
| Instance
A machine learning "example" to be used in training, testing or
performance of various machine learning algorithms.
|
| Class and Description |
|---|
| Instance
A machine learning "example" to be used in training, testing or
performance of various machine learning algorithms.
|
| Class and Description |
|---|
| InstanceList
A list of machine learning instances, typically used for training
or testing of a machine learning algorithm.
|
| Class and Description |
|---|
| Alphabet
A mapping between integers and objects where the mapping in each
direction is efficient.
|
| AugmentableFeatureVector |
| CachedMetric
Stores a hash for each object being compared for efficient
computation.
|
| ConstantMatrix |
| DenseMatrix |
| DenseVector |
| Dirichlet |
| Dirichlet.Estimator |
| FeatureConjunction |
| FeatureSelection |
| FeatureSequence
An implementation of
Sequence that ensures that every
Object in the sequence has the same class. |
| FeatureVector
A subset of an
Alphabet in which each element of the subset has an associated value. |
| FeatureVectorSequence |
| GainRatio
List of features along with their thresholds sorted in descending order of
the ratio of (1) information gained by splitting instances on the
feature at its associated threshold value, to (2) the split information.
|
| InfoGain |
| Instance
A machine learning "example" to be used in training, testing or
performance of various machine learning algorithms.
|
| InstanceList
A list of machine learning instances, typically used for training
or testing of a machine learning algorithm.
|
InstanceList.CrossValidationIterator
CrossValidationIterator allows iterating over pairs of
InstanceList, where each pair is split into training/testing
based on nfolds. |
| InstanceList.Iterator |
| Label |
| LabelAlphabet
A mapping from arbitrary objects (usually String's) to integers
(and corresponding Label objects) and back.
|
| Labeling
A distribution over possible labels for an instance.
|
| Labels
Usually some distribution over possible labels for an instance.
|
| LabelVector |
| Matrix |
| Matrix2 |
| Metric |
| Multinomial
A probability distribution over a set of features represented as a
FeatureVector. |
| Multinomial.Estimator
A hierarchy of classes used to produce estimates of probabilities, in
the form of a Multinomial, from counts associated with the elements
of an Alphabet.
|
| Multinomial.MEstimator
An Estimator in which probability estimates in a Multinomial
are generated by adding a constant m (specified at construction time)
to each count before dividing by the total of the m-biased counts.
|
| PartiallyRankedFeatureVector |
| PropertyHolder
Author: saunders Created Nov 15, 2005 Copyright (C) Univ.
|
| RankedFeatureVector |
| RankedFeatureVector.Factory |
| RankedFeatureVector.PerLabelFactory |
| Sequence |
| SequencePair |
| SparseVector
A vector that allocates memory only for non-zero values.
|
| Token
A representation of a piece of text, usually a single word, to
which we can attach properties.
|
| TokenSequence
A representation of a piece of text, usually a single word, to which we can attach properties.
|
| Vector |
| Class and Description |
|---|
| InstanceList
A list of machine learning instances, typically used for training
or testing of a machine learning algorithm.
|
| SparseVector
A vector that allocates memory only for non-zero values.
|
| Class and Description |
|---|
| InstanceList
A list of machine learning instances, typically used for training
or testing of a machine learning algorithm.
|
| Sequence |
| Class and Description |
|---|
| Alphabet
A mapping between integers and objects where the mapping in each
direction is efficient.
|
| Instance
A machine learning "example" to be used in training, testing or
performance of various machine learning algorithms.
|
| InstanceList
A list of machine learning instances, typically used for training
or testing of a machine learning algorithm.
|
| Class and Description |
|---|
| DenseVector |
| FeatureVector
A subset of an
Alphabet in which each element of the subset has an associated value. |
| Instance
A machine learning "example" to be used in training, testing or
performance of various machine learning algorithms.
|
| Matrix2 |
| Class and Description |
|---|
| Alphabet
A mapping between integers and objects where the mapping in each
direction is efficient.
|
| Instance
A machine learning "example" to be used in training, testing or
performance of various machine learning algorithms.
|
| Class and Description |
|---|
| Instance
A machine learning "example" to be used in training, testing or
performance of various machine learning algorithms.
|
| Class and Description |
|---|
| Alphabet
A mapping between integers and objects where the mapping in each
direction is efficient.
|
| DenseVector |
| FeatureVector
A subset of an
Alphabet in which each element of the subset has an associated value. |
| Instance
A machine learning "example" to be used in training, testing or
performance of various machine learning algorithms.
|
| InstanceList
A list of machine learning instances, typically used for training
or testing of a machine learning algorithm.
|
| Matrix2 |
| Sequence |
| Class and Description |
|---|
| Instance
A machine learning "example" to be used in training, testing or
performance of various machine learning algorithms.
|
| InstanceList
A list of machine learning instances, typically used for training
or testing of a machine learning algorithm.
|
| Sequence |
| TokenSequence
A representation of a piece of text, usually a single word, to which we can attach properties.
|
| Class and Description |
|---|
| Instance
A machine learning "example" to be used in training, testing or
performance of various machine learning algorithms.
|
| Class and Description |
|---|
| Instance
A machine learning "example" to be used in training, testing or
performance of various machine learning algorithms.
|
| Class and Description |
|---|
| Instance
A machine learning "example" to be used in training, testing or
performance of various machine learning algorithms.
|
| Class and Description |
|---|
| Token
A representation of a piece of text, usually a single word, to
which we can attach properties.
|
| Class and Description |
|---|
| Instance
A machine learning "example" to be used in training, testing or
performance of various machine learning algorithms.
|
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