Package | Description |
---|---|
org.tribuo |
Provides the core interfaces and classes for using Tribuo.
|
org.tribuo.anomaly |
Provides classes and infrastructure for anomaly detection problems.
|
org.tribuo.anomaly.evaluation |
Evaluation classes for anomaly detection.
|
org.tribuo.anomaly.example |
Provides a anomaly data generator used for testing implementations.
|
org.tribuo.anomaly.libsvm |
Provides an interface to LibSVM for anomaly detection problems.
|
org.tribuo.classification |
Provides classes and infrastructure for multiclass classification problems.
|
org.tribuo.classification.baseline |
Provides simple baseline multiclass classifiers.
|
org.tribuo.classification.dtree |
Provides implementations of decision trees for classification problems.
|
org.tribuo.classification.dtree.impl |
Provides internal implementation classes for classification decision trees.
|
org.tribuo.classification.ensemble |
Provides majority vote ensemble combiners for classification
along with an implementation of multiclass Adaboost.
|
org.tribuo.classification.evaluation |
Evaluation classes for multi-class classification.
|
org.tribuo.classification.example |
Provides a multiclass data generator used for testing implementations.
|
org.tribuo.classification.experiments |
Provides a set of main methods for interacting with classification tasks.
|
org.tribuo.classification.explanations |
Provides core infrastructure for local model based explanations.
|
org.tribuo.classification.explanations.lime |
Provides an implementation of LIME (Locally Interpretable Model Explanations).
|
org.tribuo.classification.liblinear |
Provides an interface to LibLinear-java for classification problems.
|
org.tribuo.classification.libsvm |
Provides an interface to LibSVM for classification problems.
|
org.tribuo.classification.mnb |
Provides an implementation of multinomial naive bayes (i.e., naive bayes for non-negative count data).
|
org.tribuo.classification.sequence |
Provides infrastructure for
SequenceModel s which
emit Label s at each step of the sequence. |
org.tribuo.classification.sequence.viterbi |
Provides an implementation of Viterbi for generating structured outputs, which can sit on top of any
Label based classification model. |
org.tribuo.classification.sgd.crf |
Provides an implementation of a linear chain CRF trained using Stochastic Gradient Descent.
|
org.tribuo.classification.sgd.kernel |
Provides a SGD implementation of a Kernel SVM using the Pegasos algorithm.
|
org.tribuo.classification.sgd.linear |
Provides an implementation of a classification linear model using Stochastic Gradient Descent.
|
org.tribuo.classification.xgboost |
Provides an interface to XGBoost for classification problems.
|
org.tribuo.clustering |
Provides classes and infrastructure for working with clustering problems.
|
org.tribuo.clustering.evaluation |
Evaluation classes for clustering.
|
org.tribuo.clustering.example |
Provides a clustering data generator used for testing implementations.
|
org.tribuo.clustering.kmeans |
Provides a multithreaded implementation of K-Means, with a
configurable distance function.
|
org.tribuo.common.liblinear |
Provides base classes for using liblinear from Tribuo.
|
org.tribuo.common.libsvm |
The base interface to LibSVM.
|
org.tribuo.common.nearest |
Provides a K-Nearest Neighbours implementation which works across
all Tribuo
Output types. |
org.tribuo.common.tree |
Provides common functionality for building decision trees, irrespective
of the predicted
Output . |
org.tribuo.common.xgboost |
Provides abstract classes for interfacing with XGBoost abstracting away all the
Output
dependent parts. |
org.tribuo.data |
Provides classes for loading in data from disk, processing it into examples, and splitting datasets for
things like cross-validation and train-test splits.
|
org.tribuo.data.columnar |
Provides classes for processing columnar data and generating
Example s. |
org.tribuo.data.columnar.processors.field |
Provides implementations of
FieldProcessor . |
org.tribuo.data.columnar.processors.response |
Provides implementations of
ResponseProcessor . |
org.tribuo.data.csv |
Provides classes which can load columnar data (using a
RowProcessor )
from a CSV (or other character delimited format) file. |
org.tribuo.data.sql |
Provides classes which can load columnar data (using a
RowProcessor )
from a SQL source. |
org.tribuo.data.text | |
org.tribuo.data.text.impl |
Provides implementations of text data processors.
|
org.tribuo.dataset |
Provides utility datasets which subsample or otherwise
transform the wrapped dataset.
|
org.tribuo.datasource |
Simple data sources for ingesting or aggregating data.
|
org.tribuo.ensemble |
Provides an interface for model prediction combinations,
two base classes for ensemble models, a base class for
ensemble excuses, and a Bagging implementation.
|
org.tribuo.evaluation |
Evaluation base classes, along with code for train/test splits and cross validation.
|
org.tribuo.evaluation.metrics |
This package contains the infrastructure classes for building evaluation metrics.
|
org.tribuo.hash |
Provides the base interface and implementations of the
Model hashing
which obscures the feature names stored in a model. |
org.tribuo.impl |
Provides implementations of base classes and interfaces from
org.tribuo . |
org.tribuo.interop |
This package contains the abstract implementation of an external model
trained by something outside of Tribuo.
|
org.tribuo.interop.onnx |
This package contains a Tribuo wrapper around the ONNX Runtime.
|
org.tribuo.interop.tensorflow |
Provides an interface to Tensorflow, allowing the training of non-sequential models using any supported
Tribuo output type.
|
org.tribuo.interop.tensorflow.sequence |
Provides an interface for working with Tensorflow sequence models, using Tribuo's
SequenceModel abstraction. |
org.tribuo.json |
Provides interop with JSON formatted data, along with tools for interacting with JSON provenance objects.
|
org.tribuo.math.la |
Provides a linear algebra system used for numerical operations in Tribuo.
|
org.tribuo.multilabel |
Provides classes and infrastructure for working with multi-label classification problems.
|
org.tribuo.multilabel.baseline | |
org.tribuo.multilabel.evaluation |
Evaluation classes for multi-label classification using
MultiLabel . |
org.tribuo.multilabel.example |
Provides a multi-label data generator for testing implementations.
|
org.tribuo.provenance |
Provides Tribuo specific infrastructure for the
Provenance system which
tracks models and datasets. |
org.tribuo.provenance.impl |
Provides internal implementations for empty provenance classes and TrainerProvenance.
|
org.tribuo.regression |
Provides classes and infrastructure for regression problems with single or multiple output dimensions.
|
org.tribuo.regression.baseline |
Provides simple baseline regression predictors.
|
org.tribuo.regression.ensemble |
Provides
EnsembleCombiner implementations
for working with multi-output regression problems. |
org.tribuo.regression.evaluation |
Evaluation classes for single or multi-dimensional regression.
|
org.tribuo.regression.example |
Provides some example regression data generators for testing implementations.
|
org.tribuo.regression.impl | |
org.tribuo.regression.liblinear |
Provides an interface to liblinear for regression problems.
|
org.tribuo.regression.libsvm |
Provides an interface to LibSVM for regression problems.
|
org.tribuo.regression.rtree |
Provides an implementation of decision trees for regression problems.
|
org.tribuo.regression.rtree.impl |
Provides internal implementation classes for the regression trees.
|
org.tribuo.regression.slm |
Provides implementations of sparse linear regression using various forms of regularisation penalty.
|
org.tribuo.regression.xgboost |
Provides an interface to XGBoost for regression problems.
|
org.tribuo.sequence |
Provides core classes for working with sequences of
Example s. |
org.tribuo.transform |
Provides infrastructure for applying transformations to a
Dataset . |
Class and Description |
---|
CategoricalIDInfo
Same as a
CategoricalInfo , but with an additional int id field. |
CategoricalInfo
Stores information about Categorical features.
|
Dataset
A class for sets of data, which are used to train and evaluate classifiers.
|
DataSource
A interface for things that can be given to a Dataset's constructor.
|
Example
An example used for training and evaluation.
|
Excuse
Holds an
Example , a Prediction and a Map from String to List of Pairs
that contains the per output explanation. |
Feature
A class for features.
|
FeatureMap
A map from Strings to
VariableInfo objects storing
information about a feature. |
ImmutableDataset
This is a
Dataset which has an ImmutableFeatureMap to store the feature information. |
ImmutableFeatureMap
ImmutableFeatureMap is used when unknown features should not be added to the FeatureMap.
|
ImmutableOutputInfo
An
OutputInfo that is fixed, and contains an id number for each valid output. |
Model
A prediction model, which is used to predict outputs for unseen instances.
|
MutableDataset
A MutableDataset is a
Dataset with a MutableFeatureMap which grows over time. |
MutableFeatureMap
A feature map that can record new feature value observations.
|
MutableOutputInfo
A mutable OutputInfo that can record observed output values.
|
Output
Output is the root interface for the supported prediction types.
|
OutputFactory
An interface associated with a specific
Output , which can generate the
appropriate Output subclass, and OutputInfo subclass. |
OutputInfo
Tracks relevant properties of the appropriate
Output subclass. |
Prediction
A prediction made by a
Model . |
RealIDInfo
Same as a
RealInfo , but with an additional int id field. |
RealInfo
Stores information about real valued features.
|
SkeletalVariableInfo
Contains information about a feature and can be stored in the feature map
in a
Dataset . |
SparseModel
A model which uses a subset of the features it knows about to make predictions.
|
Trainer
An interface for things that can train predictive models.
|
VariableIDInfo
Adds an id number to a
VariableInfo . |
VariableInfo
A VariableInfo subclass contains information about a feature and
its observed values.
|
Class and Description |
---|
ImmutableOutputInfo
An
OutputInfo that is fixed, and contains an id number for each valid output. |
MutableOutputInfo
A mutable OutputInfo that can record observed output values.
|
Output
Output is the root interface for the supported prediction types.
|
OutputFactory
An interface associated with a specific
Output , which can generate the
appropriate Output subclass, and OutputInfo subclass. |
OutputInfo
Tracks relevant properties of the appropriate
Output subclass. |
Class and Description |
---|
Model
A prediction model, which is used to predict outputs for unseen instances.
|
Prediction
A prediction made by a
Model . |
Class and Description |
---|
Dataset
A class for sets of data, which are used to train and evaluate classifiers.
|
Example
An example used for training and evaluation.
|
Class and Description |
---|
Dataset
A class for sets of data, which are used to train and evaluate classifiers.
|
Example
An example used for training and evaluation.
|
ImmutableFeatureMap
ImmutableFeatureMap is used when unknown features should not be added to the FeatureMap.
|
ImmutableOutputInfo
An
OutputInfo that is fixed, and contains an id number for each valid output. |
Model
A prediction model, which is used to predict outputs for unseen instances.
|
Prediction
A prediction made by a
Model . |
Trainer
An interface for things that can train predictive models.
|
Class and Description |
---|
ImmutableOutputInfo
An
OutputInfo that is fixed, and contains an id number for each valid output. |
Model
A prediction model, which is used to predict outputs for unseen instances.
|
MutableOutputInfo
A mutable OutputInfo that can record observed output values.
|
Output
Output is the root interface for the supported prediction types.
|
OutputFactory
An interface associated with a specific
Output , which can generate the
appropriate Output subclass, and OutputInfo subclass. |
OutputInfo
Tracks relevant properties of the appropriate
Output subclass. |
Trainer
An interface for things that can train predictive models.
|
Class and Description |
---|
Dataset
A class for sets of data, which are used to train and evaluate classifiers.
|
Example
An example used for training and evaluation.
|
Excuse
Holds an
Example , a Prediction and a Map from String to List of Pairs
that contains the per output explanation. |
Model
A prediction model, which is used to predict outputs for unseen instances.
|
Prediction
A prediction made by a
Model . |
Trainer
An interface for things that can train predictive models.
|
Class and Description |
---|
Dataset
A class for sets of data, which are used to train and evaluate classifiers.
|
SparseTrainer
Denotes this trainer emits a
SparseModel . |
Trainer
An interface for things that can train predictive models.
|
WeightedExamples
Tag interface denoting that a
Trainer can use example weights. |
Class and Description |
---|
Dataset
A class for sets of data, which are used to train and evaluate classifiers.
|
Class and Description |
---|
Dataset
A class for sets of data, which are used to train and evaluate classifiers.
|
ImmutableOutputInfo
An
OutputInfo that is fixed, and contains an id number for each valid output. |
Model
A prediction model, which is used to predict outputs for unseen instances.
|
Prediction
A prediction made by a
Model . |
Trainer
An interface for things that can train predictive models.
|
Class and Description |
---|
ImmutableOutputInfo
An
OutputInfo that is fixed, and contains an id number for each valid output. |
Model
A prediction model, which is used to predict outputs for unseen instances.
|
Prediction
A prediction made by a
Model . |
Class and Description |
---|
Dataset
A class for sets of data, which are used to train and evaluate classifiers.
|
Example
An example used for training and evaluation.
|
Class and Description |
---|
Dataset
A class for sets of data, which are used to train and evaluate classifiers.
|
Model
A prediction model, which is used to predict outputs for unseen instances.
|
Trainer
An interface for things that can train predictive models.
|
Class and Description |
---|
Example
An example used for training and evaluation.
|
Model
A prediction model, which is used to predict outputs for unseen instances.
|
Output
Output is the root interface for the supported prediction types.
|
Prediction
A prediction made by a
Model . |
Class and Description |
---|
Example
An example used for training and evaluation.
|
ImmutableFeatureMap
ImmutableFeatureMap is used when unknown features should not be added to the FeatureMap.
|
Model
A prediction model, which is used to predict outputs for unseen instances.
|
OutputFactory
An interface associated with a specific
Output , which can generate the
appropriate Output subclass, and OutputInfo subclass. |
Prediction
A prediction made by a
Model . |
SparseModel
A model which uses a subset of the features it knows about to make predictions.
|
SparseTrainer
Denotes this trainer emits a
SparseModel . |
Class and Description |
---|
Dataset
A class for sets of data, which are used to train and evaluate classifiers.
|
Example
An example used for training and evaluation.
|
Excuse
Holds an
Example , a Prediction and a Map from String to List of Pairs
that contains the per output explanation. |
ImmutableFeatureMap
ImmutableFeatureMap is used when unknown features should not be added to the FeatureMap.
|
ImmutableOutputInfo
An
OutputInfo that is fixed, and contains an id number for each valid output. |
Model
A prediction model, which is used to predict outputs for unseen instances.
|
Prediction
A prediction made by a
Model . |
Trainer
An interface for things that can train predictive models.
|
Class and Description |
---|
Dataset
A class for sets of data, which are used to train and evaluate classifiers.
|
Example
An example used for training and evaluation.
|
ImmutableFeatureMap
ImmutableFeatureMap is used when unknown features should not be added to the FeatureMap.
|
ImmutableOutputInfo
An
OutputInfo that is fixed, and contains an id number for each valid output. |
Model
A prediction model, which is used to predict outputs for unseen instances.
|
Prediction
A prediction made by a
Model . |
Trainer
An interface for things that can train predictive models.
|
Class and Description |
---|
Dataset
A class for sets of data, which are used to train and evaluate classifiers.
|
Example
An example used for training and evaluation.
|
Excuse
Holds an
Example , a Prediction and a Map from String to List of Pairs
that contains the per output explanation. |
Model
A prediction model, which is used to predict outputs for unseen instances.
|
Prediction
A prediction made by a
Model . |
Trainer
An interface for things that can train predictive models.
|
WeightedExamples
Tag interface denoting that a
Trainer can use example weights. |
Class and Description |
---|
ImmutableFeatureMap
ImmutableFeatureMap is used when unknown features should not be added to the FeatureMap.
|
ImmutableOutputInfo
An
OutputInfo that is fixed, and contains an id number for each valid output. |
Prediction
A prediction made by a
Model . |
Class and Description |
---|
Feature
A class for features.
|
Prediction
A prediction made by a
Model . |
Trainer
An interface for things that can train predictive models.
|
Class and Description |
---|
ImmutableFeatureMap
ImmutableFeatureMap is used when unknown features should not be added to the FeatureMap.
|
ImmutableOutputInfo
An
OutputInfo that is fixed, and contains an id number for each valid output. |
Output
Output is the root interface for the supported prediction types.
|
Prediction
A prediction made by a
Model . |
WeightedExamples
Tag interface denoting that a
Trainer can use example weights. |
Class and Description |
---|
Dataset
A class for sets of data, which are used to train and evaluate classifiers.
|
Example
An example used for training and evaluation.
|
Excuse
Holds an
Example , a Prediction and a Map from String to List of Pairs
that contains the per output explanation. |
Model
A prediction model, which is used to predict outputs for unseen instances.
|
Prediction
A prediction made by a
Model . |
Trainer
An interface for things that can train predictive models.
|
WeightedExamples
Tag interface denoting that a
Trainer can use example weights. |
Class and Description |
---|
Dataset
A class for sets of data, which are used to train and evaluate classifiers.
|
Example
An example used for training and evaluation.
|
Excuse
Holds an
Example , a Prediction and a Map from String to List of Pairs
that contains the per output explanation. |
Model
A prediction model, which is used to predict outputs for unseen instances.
|
Prediction
A prediction made by a
Model . |
Trainer
An interface for things that can train predictive models.
|
WeightedExamples
Tag interface denoting that a
Trainer can use example weights. |
Class and Description |
---|
Dataset
A class for sets of data, which are used to train and evaluate classifiers.
|
Example
An example used for training and evaluation.
|
ImmutableOutputInfo
An
OutputInfo that is fixed, and contains an id number for each valid output. |
Prediction
A prediction made by a
Model . |
Trainer
An interface for things that can train predictive models.
|
WeightedExamples
Tag interface denoting that a
Trainer can use example weights. |
Class and Description |
---|
ImmutableOutputInfo
An
OutputInfo that is fixed, and contains an id number for each valid output. |
MutableOutputInfo
A mutable OutputInfo that can record observed output values.
|
Output
Output is the root interface for the supported prediction types.
|
OutputFactory
An interface associated with a specific
Output , which can generate the
appropriate Output subclass, and OutputInfo subclass. |
OutputInfo
Tracks relevant properties of the appropriate
Output subclass. |
Class and Description |
---|
Model
A prediction model, which is used to predict outputs for unseen instances.
|
Prediction
A prediction made by a
Model . |
Class and Description |
---|
Dataset
A class for sets of data, which are used to train and evaluate classifiers.
|
Example
An example used for training and evaluation.
|
Class and Description |
---|
Dataset
A class for sets of data, which are used to train and evaluate classifiers.
|
Example
An example used for training and evaluation.
|
Excuse
Holds an
Example , a Prediction and a Map from String to List of Pairs
that contains the per output explanation. |
ImmutableFeatureMap
ImmutableFeatureMap is used when unknown features should not be added to the FeatureMap.
|
Model
A prediction model, which is used to predict outputs for unseen instances.
|
Prediction
A prediction made by a
Model . |
Trainer
An interface for things that can train predictive models.
|
Class and Description |
---|
Dataset
A class for sets of data, which are used to train and evaluate classifiers.
|
Example
An example used for training and evaluation.
|
Excuse
Holds an
Example , a Prediction and a Map from String to List of Pairs
that contains the per output explanation. |
ImmutableFeatureMap
ImmutableFeatureMap is used when unknown features should not be added to the FeatureMap.
|
ImmutableOutputInfo
An
OutputInfo that is fixed, and contains an id number for each valid output. |
Model
A prediction model, which is used to predict outputs for unseen instances.
|
Output
Output is the root interface for the supported prediction types.
|
Trainer
An interface for things that can train predictive models.
|
Class and Description |
---|
Dataset
A class for sets of data, which are used to train and evaluate classifiers.
|
Example
An example used for training and evaluation.
|
Excuse
Holds an
Example , a Prediction and a Map from String to List of Pairs
that contains the per output explanation. |
ImmutableFeatureMap
ImmutableFeatureMap is used when unknown features should not be added to the FeatureMap.
|
ImmutableOutputInfo
An
OutputInfo that is fixed, and contains an id number for each valid output. |
Model
A prediction model, which is used to predict outputs for unseen instances.
|
Output
Output is the root interface for the supported prediction types.
|
Trainer
An interface for things that can train predictive models.
|
Class and Description |
---|
Dataset
A class for sets of data, which are used to train and evaluate classifiers.
|
Example
An example used for training and evaluation.
|
Excuse
Holds an
Example , a Prediction and a Map from String to List of Pairs
that contains the per output explanation. |
Model
A prediction model, which is used to predict outputs for unseen instances.
|
Output
Output is the root interface for the supported prediction types.
|
Prediction
A prediction made by a
Model . |
Trainer
An interface for things that can train predictive models.
|
Class and Description |
---|
Dataset
A class for sets of data, which are used to train and evaluate classifiers.
|
Example
An example used for training and evaluation.
|
Excuse
Holds an
Example , a Prediction and a Map from String to List of Pairs
that contains the per output explanation. |
ImmutableFeatureMap
ImmutableFeatureMap is used when unknown features should not be added to the FeatureMap.
|
ImmutableOutputInfo
An
OutputInfo that is fixed, and contains an id number for each valid output. |
Model
A prediction model, which is used to predict outputs for unseen instances.
|
Output
Output is the root interface for the supported prediction types.
|
Prediction
A prediction made by a
Model . |
SparseModel
A model which uses a subset of the features it knows about to make predictions.
|
SparseTrainer
Denotes this trainer emits a
SparseModel . |
Trainer
An interface for things that can train predictive models.
|
WeightedExamples
Tag interface denoting that a
Trainer can use example weights. |
Class and Description |
---|
Dataset
A class for sets of data, which are used to train and evaluate classifiers.
|
Example
An example used for training and evaluation.
|
Excuse
Holds an
Example , a Prediction and a Map from String to List of Pairs
that contains the per output explanation. |
ImmutableFeatureMap
ImmutableFeatureMap is used when unknown features should not be added to the FeatureMap.
|
ImmutableOutputInfo
An
OutputInfo that is fixed, and contains an id number for each valid output. |
Model
A prediction model, which is used to predict outputs for unseen instances.
|
Output
Output is the root interface for the supported prediction types.
|
OutputFactory
An interface associated with a specific
Output , which can generate the
appropriate Output subclass, and OutputInfo subclass. |
Prediction
A prediction made by a
Model . |
Trainer
An interface for things that can train predictive models.
|
WeightedExamples
Tag interface denoting that a
Trainer can use example weights. |
Class and Description |
---|
ConfigurableDataSource
It's a
DataSource that's also Configurable . |
Dataset
A class for sets of data, which are used to train and evaluate classifiers.
|
Model
A prediction model, which is used to predict outputs for unseen instances.
|
Output
Output is the root interface for the supported prediction types.
|
OutputFactory
An interface associated with a specific
Output , which can generate the
appropriate Output subclass, and OutputInfo subclass. |
Trainer
An interface for things that can train predictive models.
|
Class and Description |
---|
ConfigurableDataSource
It's a
DataSource that's also Configurable . |
DataSource
A interface for things that can be given to a Dataset's constructor.
|
Example
An example used for training and evaluation.
|
Feature
A class for features.
|
ImmutableFeatureMap
ImmutableFeatureMap is used when unknown features should not be added to the FeatureMap.
|
Model
A prediction model, which is used to predict outputs for unseen instances.
|
Output
Output is the root interface for the supported prediction types.
|
OutputFactory
An interface associated with a specific
Output , which can generate the
appropriate Output subclass, and OutputInfo subclass. |
Class and Description |
---|
Feature
A class for features.
|
Class and Description |
---|
Output
Output is the root interface for the supported prediction types.
|
OutputFactory
An interface associated with a specific
Output , which can generate the
appropriate Output subclass, and OutputInfo subclass. |
Class and Description |
---|
ConfigurableDataSource
It's a
DataSource that's also Configurable . |
Dataset
A class for sets of data, which are used to train and evaluate classifiers.
|
DataSource
A interface for things that can be given to a Dataset's constructor.
|
MutableDataset
A MutableDataset is a
Dataset with a MutableFeatureMap which grows over time. |
Output
Output is the root interface for the supported prediction types.
|
OutputFactory
An interface associated with a specific
Output , which can generate the
appropriate Output subclass, and OutputInfo subclass. |
Class and Description |
---|
ConfigurableDataSource
It's a
DataSource that's also Configurable . |
DataSource
A interface for things that can be given to a Dataset's constructor.
|
Output
Output is the root interface for the supported prediction types.
|
OutputFactory
An interface associated with a specific
Output , which can generate the
appropriate Output subclass, and OutputInfo subclass. |
Class and Description |
---|
ConfigurableDataSource
It's a
DataSource that's also Configurable . |
DataSource
A interface for things that can be given to a Dataset's constructor.
|
Example
An example used for training and evaluation.
|
Feature
A class for features.
|
Output
Output is the root interface for the supported prediction types.
|
OutputFactory
An interface associated with a specific
Output , which can generate the
appropriate Output subclass, and OutputInfo subclass. |
Class and Description |
---|
ConfigurableDataSource
It's a
DataSource that's also Configurable . |
DataSource
A interface for things that can be given to a Dataset's constructor.
|
Example
An example used for training and evaluation.
|
Feature
A class for features.
|
Output
Output is the root interface for the supported prediction types.
|
OutputFactory
An interface associated with a specific
Output , which can generate the
appropriate Output subclass, and OutputInfo subclass. |
Class and Description |
---|
Dataset
A class for sets of data, which are used to train and evaluate classifiers.
|
Example
An example used for training and evaluation.
|
ImmutableDataset
This is a
Dataset which has an ImmutableFeatureMap to store the feature information. |
ImmutableFeatureMap
ImmutableFeatureMap is used when unknown features should not be added to the FeatureMap.
|
ImmutableOutputInfo
An
OutputInfo that is fixed, and contains an id number for each valid output. |
Output
Output is the root interface for the supported prediction types.
|
Class and Description |
---|
ConfigurableDataSource
It's a
DataSource that's also Configurable . |
Dataset
A class for sets of data, which are used to train and evaluate classifiers.
|
DataSource
A interface for things that can be given to a Dataset's constructor.
|
Example
An example used for training and evaluation.
|
Output
Output is the root interface for the supported prediction types.
|
OutputFactory
An interface associated with a specific
Output , which can generate the
appropriate Output subclass, and OutputInfo subclass. |
Class and Description |
---|
Dataset
A class for sets of data, which are used to train and evaluate classifiers.
|
Example
An example used for training and evaluation.
|
Excuse
Holds an
Example , a Prediction and a Map from String to List of Pairs
that contains the per output explanation. |
ImmutableFeatureMap
ImmutableFeatureMap is used when unknown features should not be added to the FeatureMap.
|
ImmutableOutputInfo
An
OutputInfo that is fixed, and contains an id number for each valid output. |
Model
A prediction model, which is used to predict outputs for unseen instances.
|
Output
Output is the root interface for the supported prediction types.
|
Prediction
A prediction made by a
Model . |
Trainer
An interface for things that can train predictive models.
|
Class and Description |
---|
Dataset
A class for sets of data, which are used to train and evaluate classifiers.
|
DataSource
A interface for things that can be given to a Dataset's constructor.
|
Example
An example used for training and evaluation.
|
Model
A prediction model, which is used to predict outputs for unseen instances.
|
Output
Output is the root interface for the supported prediction types.
|
Prediction
A prediction made by a
Model . |
Trainer
An interface for things that can train predictive models.
|
Class and Description |
---|
Dataset
A class for sets of data, which are used to train and evaluate classifiers.
|
Model
A prediction model, which is used to predict outputs for unseen instances.
|
Output
Output is the root interface for the supported prediction types.
|
Prediction
A prediction made by a
Model . |
Class and Description |
---|
Dataset
A class for sets of data, which are used to train and evaluate classifiers.
|
FeatureMap
A map from Strings to
VariableInfo objects storing
information about a feature. |
ImmutableFeatureMap
ImmutableFeatureMap is used when unknown features should not be added to the FeatureMap.
|
Model
A prediction model, which is used to predict outputs for unseen instances.
|
Output
Output is the root interface for the supported prediction types.
|
Trainer
An interface for things that can train predictive models.
|
VariableIDInfo
Adds an id number to a
VariableInfo . |
Class and Description |
---|
Example
An example used for training and evaluation.
|
Feature
A class for features.
|
FeatureMap
A map from Strings to
VariableInfo objects storing
information about a feature. |
ImmutableFeatureMap
ImmutableFeatureMap is used when unknown features should not be added to the FeatureMap.
|
ImmutableOutputInfo
An
OutputInfo that is fixed, and contains an id number for each valid output. |
Output
Output is the root interface for the supported prediction types.
|
Class and Description |
---|
Example
An example used for training and evaluation.
|
Excuse
Holds an
Example , a Prediction and a Map from String to List of Pairs
that contains the per output explanation. |
ImmutableFeatureMap
ImmutableFeatureMap is used when unknown features should not be added to the FeatureMap.
|
ImmutableOutputInfo
An
OutputInfo that is fixed, and contains an id number for each valid output. |
Model
A prediction model, which is used to predict outputs for unseen instances.
|
Output
Output is the root interface for the supported prediction types.
|
OutputFactory
An interface associated with a specific
Output , which can generate the
appropriate Output subclass, and OutputInfo subclass. |
Prediction
A prediction made by a
Model . |
Class and Description |
---|
Example
An example used for training and evaluation.
|
ImmutableOutputInfo
An
OutputInfo that is fixed, and contains an id number for each valid output. |
Model
A prediction model, which is used to predict outputs for unseen instances.
|
Output
Output is the root interface for the supported prediction types.
|
OutputFactory
An interface associated with a specific
Output , which can generate the
appropriate Output subclass, and OutputInfo subclass. |
Prediction
A prediction made by a
Model . |
Class and Description |
---|
Dataset
A class for sets of data, which are used to train and evaluate classifiers.
|
Example
An example used for training and evaluation.
|
Excuse
Holds an
Example , a Prediction and a Map from String to List of Pairs
that contains the per output explanation. |
ImmutableFeatureMap
ImmutableFeatureMap is used when unknown features should not be added to the FeatureMap.
|
Model
A prediction model, which is used to predict outputs for unseen instances.
|
Output
Output is the root interface for the supported prediction types.
|
OutputFactory
An interface associated with a specific
Output , which can generate the
appropriate Output subclass, and OutputInfo subclass. |
Prediction
A prediction made by a
Model . |
Trainer
An interface for things that can train predictive models.
|
Class and Description |
---|
ImmutableFeatureMap
ImmutableFeatureMap is used when unknown features should not be added to the FeatureMap.
|
ImmutableOutputInfo
An
OutputInfo that is fixed, and contains an id number for each valid output. |
Output
Output is the root interface for the supported prediction types.
|
Prediction
A prediction made by a
Model . |
Class and Description |
---|
ConfigurableDataSource
It's a
DataSource that's also Configurable . |
DataSource
A interface for things that can be given to a Dataset's constructor.
|
Output
Output is the root interface for the supported prediction types.
|
Class and Description |
---|
Dataset
A class for sets of data, which are used to train and evaluate classifiers.
|
Example
An example used for training and evaluation.
|
ImmutableFeatureMap
ImmutableFeatureMap is used when unknown features should not be added to the FeatureMap.
|
Output
Output is the root interface for the supported prediction types.
|
Class and Description |
---|
ImmutableOutputInfo
An
OutputInfo that is fixed, and contains an id number for each valid output. |
MutableOutputInfo
A mutable OutputInfo that can record observed output values.
|
Output
Output is the root interface for the supported prediction types.
|
OutputFactory
An interface associated with a specific
Output , which can generate the
appropriate Output subclass, and OutputInfo subclass. |
OutputInfo
Tracks relevant properties of the appropriate
Output subclass. |
Class and Description |
---|
Dataset
A class for sets of data, which are used to train and evaluate classifiers.
|
Example
An example used for training and evaluation.
|
Excuse
Holds an
Example , a Prediction and a Map from String to List of Pairs
that contains the per output explanation. |
Model
A prediction model, which is used to predict outputs for unseen instances.
|
Prediction
A prediction made by a
Model . |
Trainer
An interface for things that can train predictive models.
|
Class and Description |
---|
ImmutableOutputInfo
An
OutputInfo that is fixed, and contains an id number for each valid output. |
Model
A prediction model, which is used to predict outputs for unseen instances.
|
Prediction
A prediction made by a
Model . |
Class and Description |
---|
Dataset
A class for sets of data, which are used to train and evaluate classifiers.
|
Example
An example used for training and evaluation.
|
Class and Description |
---|
Dataset
A class for sets of data, which are used to train and evaluate classifiers.
|
OutputFactory
An interface associated with a specific
Output , which can generate the
appropriate Output subclass, and OutputInfo subclass. |
Trainer
An interface for things that can train predictive models.
|
Class and Description |
---|
Trainer
An interface for things that can train predictive models.
|
Class and Description |
---|
ImmutableOutputInfo
An
OutputInfo that is fixed, and contains an id number for each valid output. |
MutableOutputInfo
A mutable OutputInfo that can record observed output values.
|
Output
Output is the root interface for the supported prediction types.
|
OutputFactory
An interface associated with a specific
Output , which can generate the
appropriate Output subclass, and OutputInfo subclass. |
OutputInfo
Tracks relevant properties of the appropriate
Output subclass. |
Class and Description |
---|
Dataset
A class for sets of data, which are used to train and evaluate classifiers.
|
Example
An example used for training and evaluation.
|
Excuse
Holds an
Example , a Prediction and a Map from String to List of Pairs
that contains the per output explanation. |
Model
A prediction model, which is used to predict outputs for unseen instances.
|
Prediction
A prediction made by a
Model . |
Trainer
An interface for things that can train predictive models.
|
Class and Description |
---|
ImmutableOutputInfo
An
OutputInfo that is fixed, and contains an id number for each valid output. |
Prediction
A prediction made by a
Model . |
Class and Description |
---|
ImmutableOutputInfo
An
OutputInfo that is fixed, and contains an id number for each valid output. |
Model
A prediction model, which is used to predict outputs for unseen instances.
|
Prediction
A prediction made by a
Model . |
Class and Description |
---|
ConfigurableDataSource
It's a
DataSource that's also Configurable . |
Dataset
A class for sets of data, which are used to train and evaluate classifiers.
|
DataSource
A interface for things that can be given to a Dataset's constructor.
|
Example
An example used for training and evaluation.
|
OutputFactory
An interface associated with a specific
Output , which can generate the
appropriate Output subclass, and OutputInfo subclass. |
Class and Description |
---|
Dataset
A class for sets of data, which are used to train and evaluate classifiers.
|
Example
An example used for training and evaluation.
|
ImmutableFeatureMap
ImmutableFeatureMap is used when unknown features should not be added to the FeatureMap.
|
ImmutableOutputInfo
An
OutputInfo that is fixed, and contains an id number for each valid output. |
Model
A prediction model, which is used to predict outputs for unseen instances.
|
Prediction
A prediction made by a
Model . |
SparseModel
A model which uses a subset of the features it knows about to make predictions.
|
SparseTrainer
Denotes this trainer emits a
SparseModel . |
Trainer
An interface for things that can train predictive models.
|
Class and Description |
---|
Dataset
A class for sets of data, which are used to train and evaluate classifiers.
|
Example
An example used for training and evaluation.
|
Excuse
Holds an
Example , a Prediction and a Map from String to List of Pairs
that contains the per output explanation. |
ImmutableFeatureMap
ImmutableFeatureMap is used when unknown features should not be added to the FeatureMap.
|
ImmutableOutputInfo
An
OutputInfo that is fixed, and contains an id number for each valid output. |
Model
A prediction model, which is used to predict outputs for unseen instances.
|
Prediction
A prediction made by a
Model . |
Trainer
An interface for things that can train predictive models.
|
Class and Description |
---|
Dataset
A class for sets of data, which are used to train and evaluate classifiers.
|
Example
An example used for training and evaluation.
|
ImmutableFeatureMap
ImmutableFeatureMap is used when unknown features should not be added to the FeatureMap.
|
ImmutableOutputInfo
An
OutputInfo that is fixed, and contains an id number for each valid output. |
Model
A prediction model, which is used to predict outputs for unseen instances.
|
Prediction
A prediction made by a
Model . |
Trainer
An interface for things that can train predictive models.
|
Class and Description |
---|
Dataset
A class for sets of data, which are used to train and evaluate classifiers.
|
Example
An example used for training and evaluation.
|
Excuse
Holds an
Example , a Prediction and a Map from String to List of Pairs
that contains the per output explanation. |
Model
A prediction model, which is used to predict outputs for unseen instances.
|
Prediction
A prediction made by a
Model . |
SparseModel
A model which uses a subset of the features it knows about to make predictions.
|
SparseTrainer
Denotes this trainer emits a
SparseModel . |
Trainer
An interface for things that can train predictive models.
|
WeightedExamples
Tag interface denoting that a
Trainer can use example weights. |
Class and Description |
---|
Dataset
A class for sets of data, which are used to train and evaluate classifiers.
|
ImmutableFeatureMap
ImmutableFeatureMap is used when unknown features should not be added to the FeatureMap.
|
ImmutableOutputInfo
An
OutputInfo that is fixed, and contains an id number for each valid output. |
Class and Description |
---|
Dataset
A class for sets of data, which are used to train and evaluate classifiers.
|
Example
An example used for training and evaluation.
|
Excuse
Holds an
Example , a Prediction and a Map from String to List of Pairs
that contains the per output explanation. |
Model
A prediction model, which is used to predict outputs for unseen instances.
|
SparseModel
A model which uses a subset of the features it knows about to make predictions.
|
SparseTrainer
Denotes this trainer emits a
SparseModel . |
Trainer
An interface for things that can train predictive models.
|
WeightedExamples
Tag interface denoting that a
Trainer can use example weights. |
Class and Description |
---|
Dataset
A class for sets of data, which are used to train and evaluate classifiers.
|
Example
An example used for training and evaluation.
|
ImmutableOutputInfo
An
OutputInfo that is fixed, and contains an id number for each valid output. |
Prediction
A prediction made by a
Model . |
Trainer
An interface for things that can train predictive models.
|
WeightedExamples
Tag interface denoting that a
Trainer can use example weights. |
Class and Description |
---|
Dataset
A class for sets of data, which are used to train and evaluate classifiers.
|
Example
An example used for training and evaluation.
|
Feature
A class for features.
|
FeatureMap
A map from Strings to
VariableInfo objects storing
information about a feature. |
ImmutableFeatureMap
ImmutableFeatureMap is used when unknown features should not be added to the FeatureMap.
|
ImmutableOutputInfo
An
OutputInfo that is fixed, and contains an id number for each valid output. |
MutableFeatureMap
A feature map that can record new feature value observations.
|
MutableOutputInfo
A mutable OutputInfo that can record observed output values.
|
Output
Output is the root interface for the supported prediction types.
|
OutputFactory
An interface associated with a specific
Output , which can generate the
appropriate Output subclass, and OutputInfo subclass. |
OutputInfo
Tracks relevant properties of the appropriate
Output subclass. |
Prediction
A prediction made by a
Model . |
Class and Description |
---|
Dataset
A class for sets of data, which are used to train and evaluate classifiers.
|
Example
An example used for training and evaluation.
|
Excuse
Holds an
Example , a Prediction and a Map from String to List of Pairs
that contains the per output explanation. |
FeatureMap
A map from Strings to
VariableInfo objects storing
information about a feature. |
Model
A prediction model, which is used to predict outputs for unseen instances.
|
MutableDataset
A MutableDataset is a
Dataset with a MutableFeatureMap which grows over time. |
Output
Output is the root interface for the supported prediction types.
|
Prediction
A prediction made by a
Model . |
Trainer
An interface for things that can train predictive models.
|
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