Uses of Interface
org.tribuo.Output

Packages that use Output

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.classification	Provides classes and infrastructure for multiclass classification problems.
org.tribuo.classification.explanations	Provides core infrastructure for local model based explanations.
org.tribuo.classification.sgd.crf	Provides an implementation of a linear chain CRF trained using Stochastic Gradient Descent.
org.tribuo.clustering	Provides classes and infrastructure for working with clustering problems.
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.sgd	Provides the base classes for models trained with stochastic gradient descent.
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 Examples.
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	Provides interfaces for converting text inputs into Features and Examples.
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.oci	Code for uploading models to Oracle Cloud Infrastructure Data Science, and also for scoring models deployed in Oracle Cloud Infrastructure Data Science.
org.tribuo.interop.onnx	This package contains a Tribuo wrapper around the ONNX Runtime.
org.tribuo.interop.onnx.extractors	Provides feature extraction implementations which use ONNX models.
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.regression	Provides classes and infrastructure for regression problems with single or multiple output dimensions.
org.tribuo.reproducibility	Reproducibility utility based on Tribuo's provenance objects.
org.tribuo.sequence	Provides core classes for working with sequences of Examples.
org.tribuo.transform	Provides infrastructure for applying transformations to a Dataset.

Uses of Output in org.tribuo

Classes in org.tribuo with type parameters of type Output

Modifier and Type	Interface	Description
interface	ConfigurableDataSource<T extends Output<T>>	It's a DataSource that's also Configurable.
class	Dataset<T extends Output<T>>	A class for sets of data, which are used to train and evaluate classifiers.
interface	DataSource<T extends Output<T>>	A interface for things that can be given to a Dataset's constructor.
class	Example<T extends Output<T>>	An example used for training and evaluation.
class	Excuse<T extends Output<T>>	Holds an Example, a Prediction and a Map from String to List of Pairs that contains the per output explanation.
class	ImmutableDataset<T extends Output<T>>	This is a Dataset which has an ImmutableFeatureMap to store the feature information.
interface	ImmutableOutputInfo<T extends Output<T>>	An OutputInfo that is fixed, and contains an id number for each valid output.
interface	IncrementalTrainer<T extends Output<T>,U extends Model<T>>	An interface for incremental training of Models.
class	Model<T extends Output<T>>	A prediction model, which is used to predict outputs for unseen instances.
class	MutableDataset<T extends Output<T>>	A MutableDataset is a Dataset with a MutableFeatureMap which grows over time.
interface	MutableOutputInfo<T extends Output<T>>	A mutable OutputInfo that can record observed output values.
interface	Output<T extends Output<T>>	Output is the root interface for the supported prediction types.
interface	OutputFactory<T extends Output<T>>	An interface associated with a specific Output, which can generate the appropriate Output subclass, and OutputInfo subclass.
interface	OutputInfo<T extends Output<T>>	Tracks relevant properties of the appropriate Output subclass.
class	Prediction<T extends Output<T>>	A prediction made by a Model.
class	SparseModel<T extends Output<T>>	A model which uses a subset of the features it knows about to make predictions.
interface	SparseTrainer<T extends Output<T>>	Denotes this trainer emits a SparseModel.
interface	Trainer<T extends Output<T>>	An interface for things that can train predictive models.

Fields in org.tribuo declared as Output

Modifier and Type	Field	Description
protected final T	Example.output	The output associated with this example.

Methods in org.tribuo with type parameters of type Output

Modifier and Type	Method	Description
static <T extends Output<T>> Dataset<T>	Dataset.castDataset(Dataset<?> inputDataset, Class<T> outputType)	Casts the dataset to the specified output type, assuming it is valid.
<U extends Output<U>> Model<U>	Model.castModel(Class<U> outputType)	Casts the model to the specified output type, assuming it is valid.
static <T extends Output<T>> ImmutableDataset<T>	ImmutableDataset.copyDataset(Dataset<T> dataset)	Creates an immutable deep copy of the supplied dataset.
static <T extends Output<T>> ImmutableDataset<T>	ImmutableDataset.copyDataset(Dataset<T> dataset, ImmutableFeatureMap featureIDMap, ImmutableOutputInfo<T> outputIDInfo)	Creates an immutable deep copy of the supplied dataset, using a different feature and output map.
static <T extends Output<T>> ImmutableDataset<T>	ImmutableDataset.copyDataset(Dataset<T> dataset, ImmutableFeatureMap featureIDMap, ImmutableOutputInfo<T> outputIDInfo, Merger merger)	Creates an immutable deep copy of the supplied dataset.
static <T extends Output<T>> MutableDataset<T>	MutableDataset.createDeepCopy(Dataset<T> other)	Creates a deep copy of the supplied Dataset which is mutable.
static <T extends Output<T>> ImmutableDataset<T>	ImmutableDataset.hashFeatureMap(Dataset<T> dataset, Hasher hasher)	Creates an immutable shallow copy of the supplied dataset, using the hasher to generate a HashedFeatureMap which transparently maps from the feature name to the hashed variant.
static <T extends Output<T>> void	OutputFactory.validateMapping(Map<T,Integer> mapping)	Validates that the mapping can be used as an output info, i.e.

Method parameters in org.tribuo with type arguments of type Output

Modifier and Type	Method	Description
boolean	Dataset.validate(Class<? extends Output<?>> clazz)	Validates that this Dataset does in fact contain the supplied output type.
boolean	Model.validate(Class<? extends Output<?>> clazz)	Validates that this Model does in fact support the supplied output type.

Uses of Output in org.tribuo.anomaly

Classes in org.tribuo.anomaly that implement Output

Modifier and Type	Class	Description
final class	Event	An Output representing either an Event.EventType.ANOMALOUS or an Event.EventType.EXPECTED event.

Uses of Output in org.tribuo.classification

Subinterfaces of Output in org.tribuo.classification

Modifier and Type	Interface	Description
interface	Classifiable<T extends Classifiable<T>>	A tag interface for multi-class and multi-label classification tasks.

Classes in org.tribuo.classification that implement Output

Modifier and Type	Class	Description
final class	Label	An immutable multi-class classification label.

Uses of Output in org.tribuo.classification.explanations

Classes in org.tribuo.classification.explanations with type parameters of type Output

Modifier and Type	Interface	Description
interface	ColumnarExplainer<T extends Output<T>>	An explainer for data using Tribuo's columnar data package.
interface	Explanation<T extends Output<T>>	An explanation knows what features are used, what the explaining Model is and what the original Model's prediction is.
interface	TabularExplainer<T extends Output<T>>	An explainer for tabular data.
interface	TextExplainer<T extends Output<T>>	An explainer for text data.

Uses of Output in org.tribuo.classification.sgd.crf

Methods in org.tribuo.classification.sgd.crf with type parameters of type Output

Modifier and Type	Method	Description
static <T extends Output<T>> SparseVector[]	CRFModel.convert(SequenceExample<T> example, ImmutableFeatureMap featureIDMap)	Deprecated. As it's replaced with CRFModel.convertToVector(org.tribuo.sequence.SequenceExample<T>, org.tribuo.ImmutableFeatureMap) which is more flexible.
static <T extends Output<T>> SGDVector[]	CRFModel.convertToVector(SequenceExample<T> example, ImmutableFeatureMap featureIDMap)	Converts a SequenceExample into an array of SGDVectors suitable for CRF prediction.

Uses of Output in org.tribuo.clustering

Classes in org.tribuo.clustering that implement Output

Modifier and Type	Class	Description
class	ClusterID	A clustering id.

Uses of Output in org.tribuo.common.liblinear

Classes in org.tribuo.common.liblinear with type parameters of type Output

Modifier and Type	Class	Description
class	LibLinearModel<T extends Output<T>>	A Model which wraps a LibLinear-java model.
class	LibLinearTrainer<T extends Output<T>>	A Trainer which wraps a liblinear-java trainer.
interface	LibLinearType<T extends Output<T>>	A carrier type for the liblinear algorithm type.

Methods in org.tribuo.common.liblinear with type parameters of type Output

Modifier and Type	Method	Description
static <T extends Output<T>> de.bwaldvogel.liblinear.FeatureNode[]	LibLinearTrainer.exampleToNodes(Example<T> example, ImmutableFeatureMap featureIDMap, List<de.bwaldvogel.liblinear.FeatureNode> features)	Converts a Tribuo Example into a liblinear FeatureNode array, including a bias feature.

Uses of Output in org.tribuo.common.libsvm

Classes in org.tribuo.common.libsvm with type parameters of type Output

Modifier and Type	Class	Description
class	LibSVMModel<T extends Output<T>>	A model that uses an underlying libSVM model to make the predictions.
class	LibSVMTrainer<T extends Output<T>>	A trainer that will train using libsvm's Java implementation.
class	SVMParameters<T extends Output<T>>	A container for SVM parameters and the kernel.
interface	SVMType<T extends Output<T>>	A carrier type for the SVM type.

Methods in org.tribuo.common.libsvm with type parameters of type Output

Modifier and Type	Method	Description
static <T extends Output<T>> libsvm.svm_node[]	LibSVMTrainer.exampleToNodes(Example<T> example, ImmutableFeatureMap featureIDMap, List<libsvm.svm_node> features)	Convert the example into an array of svm_node which represents a sparse feature vector.

Uses of Output in org.tribuo.common.nearest

Classes in org.tribuo.common.nearest with type parameters of type Output

Modifier and Type	Class	Description
class	KNNModel<T extends Output<T>>	A k-nearest neighbours model.
class	KNNTrainer<T extends Output<T>>	A Trainer for k-nearest neighbour models.

Uses of Output in org.tribuo.common.sgd

Classes in org.tribuo.common.sgd with type parameters of type Output

Modifier and Type	Class	Description
class	AbstractFMModel<T extends Output<T>>	A quadratic factorization machine model trained using SGD.
class	AbstractFMTrainer<T extends Output<T>,U,V extends AbstractFMModel<T>>	A trainer for a quadratic factorization machine model which uses SGD.
class	AbstractLinearSGDModel<T extends Output<T>>	A linear model trained using SGD.
class	AbstractLinearSGDTrainer<T extends Output<T>,U,V extends AbstractLinearSGDModel<T>>	A trainer for a linear model which uses SGD.
class	AbstractSGDModel<T extends Output<T>>	A model trained using SGD.
class	AbstractSGDTrainer<T extends Output<T>,U,V extends Model<T>,X extends FeedForwardParameters>	A trainer for a model which uses SGD.

Uses of Output in org.tribuo.common.tree

Classes in org.tribuo.common.tree with type parameters of type Output

Modifier and Type	Class	Description
class	AbstractCARTTrainer<T extends Output<T>>	Base class for Trainer's that use an approximation of the CART algorithm to build a decision tree.
class	AbstractTrainingNode<T extends Output<T>>	Base class for decision tree nodes used at training time.
interface	DecisionTreeTrainer<T extends Output<T>>	A tag interface for a Trainer so the random forests trainer can check if it's actually a tree.
class	ExtraTreesTrainer<T extends Output<T>>	A trainer which produces an Extremely Randomized Tree Ensemble.
class	LeafNode<T extends Output<T>>	An immutable leaf Node that can create a prediction.
interface	Node<T extends Output<T>>	A node in a decision tree.
class	RandomForestTrainer<T extends Output<T>>	A trainer which produces a random forest.
class	SplitNode<T extends Output<T>>	An immutable Node with a split and two child nodes.
class	TreeModel<T extends Output<T>>	A Model wrapped around a decision tree root Node.

Methods in org.tribuo.common.tree with type parameters of type Output

Modifier and Type	Method	Description
protected static <T extends Output<T>> int	TreeModel.computeDepth(int initialDepth, Node<T> root)

Uses of Output in org.tribuo.common.xgboost

Classes in org.tribuo.common.xgboost with type parameters of type Output

Modifier and Type	Class	Description
final class	XGBoostExternalModel<T extends Output<T>>	A Model which wraps around a XGBoost.Booster which was trained by a system other than Tribuo.
final class	XGBoostModel<T extends Output<T>>	A Model which wraps around a XGBoost.Booster.
interface	XGBoostOutputConverter<T extends Output<T>>	Converts the output of XGBoost into the appropriate prediction type.
class	XGBoostTrainer<T extends Output<T>>	A Trainer which wraps the XGBoost training procedure.
protected static class	XGBoostTrainer.DMatrixTuple<T extends Output<T>>	Tuple of a DMatrix, the number of valid features in each example, and the examples themselves.

Methods in org.tribuo.common.xgboost with type parameters of type Output

Modifier and Type	Method	Description
protected static <T extends Output<T>> XGBoostTrainer.DMatrixTuple<T>	XGBoostTrainer.convertDataset(Dataset<T> examples)
protected static <T extends Output<T>> XGBoostTrainer.DMatrixTuple<T>	XGBoostTrainer.convertDataset(Dataset<T> examples, Function<T,Float> responseExtractor)
protected static <T extends Output<T>> XGBoostTrainer.DMatrixTuple<T>	XGBoostTrainer.convertExample(Example<T> example, ImmutableFeatureMap featureMap)
protected static <T extends Output<T>> XGBoostTrainer.DMatrixTuple<T>	XGBoostTrainer.convertExample(Example<T> example, ImmutableFeatureMap featureMap, Function<T,Float> responseExtractor)	Converts an examples into a DMatrix.
protected static <T extends Output<T>> XGBoostTrainer.DMatrixTuple<T>	XGBoostTrainer.convertExamples(Iterable<Example<T>> examples, ImmutableFeatureMap featureMap)
protected static <T extends Output<T>> XGBoostTrainer.DMatrixTuple<T>	XGBoostTrainer.convertExamples(Iterable<Example<T>> examples, ImmutableFeatureMap featureMap, Function<T,Float> responseExtractor)	Converts an iterable of examples into a DMatrix.
protected static <T extends Output<T>> long	XGBoostTrainer.convertSingleExample(Example<T> example, ImmutableFeatureMap featureMap, ArrayList<Float> dataList, ArrayList<Integer> indicesList, ArrayList<Long> headersList, long header)	Writes out the features from an example into the three supplied ArrayLists.
static <T extends Output<T>> XGBoostExternalModel<T>	XGBoostExternalModel.createXGBoostModel(OutputFactory<T> factory, Map<String,Integer> featureMapping, Map<T,Integer> outputMapping, XGBoostOutputConverter<T> outputFunc, String path)	Creates an XGBoostExternalModel from the supplied model on disk.
static <T extends Output<T>> XGBoostExternalModel<T>	XGBoostExternalModel.createXGBoostModel(OutputFactory<T> factory, Map<String,Integer> featureMapping, Map<T,Integer> outputMapping, XGBoostOutputConverter<T> outputFunc, Path path)	Creates an XGBoostExternalModel from the supplied model on disk.
static <T extends Output<T>> XGBoostExternalModel<T>	XGBoostExternalModel.createXGBoostModel(OutputFactory<T> factory, Map<String,Integer> featureMapping, Map<T,Integer> outputMapping, XGBoostOutputConverter<T> outputFunc, ml.dmlc.xgboost4j.java.Booster model, URL provenanceLocation)	Deprecated. As the URL argument must always be valid.
static <T extends Output<T>> XGBoostExternalModel<T>	XGBoostExternalModel.createXGBoostModel(OutputFactory<T> factory, Map<String,Integer> featureMapping, Map<T,Integer> outputMapping, XGBoostOutputConverter<T> outputFunc, ml.dmlc.xgboost4j.java.Booster model, Map<String,com.oracle.labs.mlrg.olcut.provenance.Provenance> instanceProvenance)	Creates an XGBoostExternalModel from the supplied in-memory XGBoost Booster.

Uses of Output in org.tribuo.data

Fields in org.tribuo.data with type parameters of type Output

Modifier and Type	Field	Description
ConfigurableDataSource<? extends Output<?>>	PreprocessAndSerialize.PreprocessAndSerializeOptions.dataSource	Datasource to load from a config file

Methods in org.tribuo.data with type parameters of type Output

Modifier and Type	Method	Description
<T extends Output<T>> com.oracle.labs.mlrg.olcut.util.Pair<Dataset<T>,Dataset<T>>	DataOptions.load(OutputFactory<T> outputFactory)	Loads the training and testing data from DataOptions.trainingPath and DataOptions.testingPath according to the other parameters specified in this class.
static <T extends Output<T>> void	CompletelyConfigurableTrainTest.main(String[] args)
static <T extends Output<T>> void	ConfigurableTrainTest.main(String[] args)
<T extends Output<T>> void	DataOptions.saveModel(Model<T> model)	Saves the model out to the path in DataOptions.outputPath.

Uses of Output in org.tribuo.data.columnar

Classes in org.tribuo.data.columnar with type parameters of type Output

Modifier and Type	Class	Description
class	ColumnarDataSource<T extends Output<T>>	A ConfigurableDataSource base class which takes columnar data (e.g., csv or DB table rows) and generates Examples.
interface	ResponseProcessor<T extends Output<T>>	An interface that will take the response field and produce an Output.
class	RowProcessor<T extends Output<T>>	A processor which takes a Map of String to String and returns an Example.

Uses of Output in org.tribuo.data.columnar.processors.response

Classes in org.tribuo.data.columnar.processors.response with type parameters of type Output

Modifier and Type	Class	Description
class	BinaryResponseProcessor<T extends Output<T>>	A ResponseProcessor that takes a single value of the field as the positive class and all other values as the negative class.
final class	EmptyResponseProcessor<T extends Output<T>>	A ResponseProcessor that always emits an empty optional.
class	FieldResponseProcessor<T extends Output<T>>	A response processor that returns the value(s) in a given (set of) fields.
class	QuartileResponseProcessor<T extends Output<T>>	Processes the response into quartiles and emits them as classification outputs.

Uses of Output in org.tribuo.data.csv

Classes in org.tribuo.data.csv with type parameters of type Output

Modifier and Type	Class	Description
class	CSVDataSource<T extends Output<T>>	A DataSource for loading separable data from a text file (e.g., CSV, TSV) and applying FieldProcessors to it.
class	CSVLoader<T extends Output<T>>	Load a DataSource/Dataset from a CSV file.

Methods in org.tribuo.data.csv with type parameters of type Output

Modifier and Type	Method	Description
<T extends Output<T>> void	CSVSaver.save(Path csvPath, Dataset<T> dataset, String responseName)	Saves the dataset to the specified path.
<T extends Output<T>> void	CSVSaver.save(Path csvPath, Dataset<T> dataset, Set<String> responseNames)	Saves the dataset to the specified path.

Uses of Output in org.tribuo.data.sql

Classes in org.tribuo.data.sql with type parameters of type Output

Modifier and Type	Class	Description
class	SQLDataSource<T extends Output<T>>	A DataSource for loading columnar data from a database and applying FieldProcessors to it.

Uses of Output in org.tribuo.data.text

Classes in org.tribuo.data.text with type parameters of type Output

Modifier and Type	Class	Description
class	DirectoryFileSource<T extends Output<T>>	A data source for a somewhat-common format for text classification datasets: a top level directory that contains a number of subdirectories.
class	TextDataSource<T extends Output<T>>	A base class for textual data sets.
interface	TextFeatureExtractor<T extends Output<T>>	An interface for things that take text and turn them into examples that we can use to train or evaluate a classifier.

Uses of Output in org.tribuo.data.text.impl

Classes in org.tribuo.data.text.impl with type parameters of type Output

Modifier and Type	Class	Description
class	SimpleStringDataSource<T extends Output<T>>	A version of SimpleTextDataSource that accepts a List of Strings.
class	SimpleTextDataSource<T extends Output<T>>	A dataset for a simple data format for text classification experiments.
class	TextFeatureExtractorImpl<T extends Output<T>>	An implementation of TextFeatureExtractor that takes a TextPipeline and generates ArrayExample.

Uses of Output in org.tribuo.dataset

Classes in org.tribuo.dataset with type parameters of type Output

Modifier and Type	Class	Description
final class	DatasetView<T extends Output<T>>	DatasetView provides an immutable view on another Dataset that only exposes selected examples.
class	MinimumCardinalityDataset<T extends Output<T>>	This class creates a pruned dataset in which low frequency features that occur less than the provided minimum cardinality have been removed.

Methods in org.tribuo.dataset with type parameters of type Output

Modifier and Type	Method	Description
static <T extends Output<T>> DatasetView<T>	DatasetView.createBootstrapView(Dataset<T> dataset, int size, long seed)	Generates a DatasetView bootstrapped from the supplied Dataset.
static <T extends Output<T>> DatasetView<T>	DatasetView.createBootstrapView(Dataset<T> dataset, int size, long seed, ImmutableFeatureMap featureIDs, ImmutableOutputInfo<T> outputIDs)	Generates a DatasetView bootstrapped from the supplied Dataset.
static <T extends Output<T>> DatasetView<T>	DatasetView.createView(Dataset<T> dataset, Predicate<Example<T>> predicate, String tag)	Creates a view from the supplied dataset, using the specified predicate to test if each example should be in this view.
static <T extends Output<T>> DatasetView<T>	DatasetView.createWeightedBootstrapView(Dataset<T> dataset, int size, long seed, float[] exampleWeights)	Generates a DatasetView bootstrapped from the supplied Dataset using the supplied example weights.
static <T extends Output<T>> DatasetView<T>	DatasetView.createWeightedBootstrapView(Dataset<T> dataset, int size, long seed, float[] exampleWeights, ImmutableFeatureMap featureIDs, ImmutableOutputInfo<T> outputIDs)	Generates a DatasetView bootstrapped from the supplied Dataset using the supplied example weights.

Uses of Output in org.tribuo.datasource

Classes in org.tribuo.datasource with type parameters of type Output

Modifier and Type	Class	Description
class	AggregateConfigurableDataSource<T extends Output<T>>	Aggregates multiple ConfigurableDataSources, uses AggregateDataSource.IterationOrder to control the iteration order.
class	AggregateDataSource<T extends Output<T>>	Aggregates multiple DataSources, uses AggregateDataSource.IterationOrder to control the iteration order.
final class	IDXDataSource<T extends Output<T>>	A DataSource which can read IDX formatted data (i.e., MNIST).
final class	LibSVMDataSource<T extends Output<T>>	A DataSource which can read LibSVM formatted data.
class	ListDataSource<T extends Output<T>>	A data source which wraps up a list of Examples along with their DataSourceProvenance and an OutputFactory.

Methods in org.tribuo.datasource with type parameters of type Output

Modifier and Type	Method	Description
static <T extends Output<T>> void	LibSVMDataSource.writeLibSVMFormat(Dataset<T> dataset, PrintStream out, boolean zeroIndexed, Function<T,Number> transformationFunc)	Writes out a dataset in LibSVM format.

Uses of Output in org.tribuo.ensemble

Classes in org.tribuo.ensemble with type parameters of type Output

Modifier and Type	Class	Description
class	BaggingTrainer<T extends Output<T>>	A Trainer that wraps another trainer and produces a bagged ensemble.
interface	EnsembleCombiner<T extends Output<T>>	An interface for combining predictions.
class	EnsembleExcuse<T extends Output<T>>	An Excuse which has a List of excuses for each of the ensemble members.
class	EnsembleModel<T extends Output<T>>	A model which contains a list of other Models.
final class	WeightedEnsembleModel<T extends Output<T>>	An ensemble model that uses weights to combine the ensemble member predictions.

Methods in org.tribuo.ensemble with type parameters of type Output

Modifier and Type	Method	Description
static <T extends Output<T>> WeightedEnsembleModel<T>	WeightedEnsembleModel.createEnsembleFromExistingModels(String name, List<Model<T>> models, EnsembleCombiner<T> combiner)	Creates an ensemble from existing models.
static <T extends Output<T>> WeightedEnsembleModel<T>	WeightedEnsembleModel.createEnsembleFromExistingModels(String name, List<Model<T>> models, EnsembleCombiner<T> combiner, float[] weights)	Creates an ensemble from existing models.

Uses of Output in org.tribuo.evaluation

Classes in org.tribuo.evaluation with type parameters of type Output

Modifier and Type	Class	Description
class	AbstractEvaluator<T extends Output<T>,C extends MetricContext<T>,E extends Evaluation<T>,M extends EvaluationMetric<T,C>>	Base class for evaluators.
class	CrossValidation<T extends Output<T>,E extends Evaluation<T>>	A class that does k-fold cross-validation.
interface	Evaluation<T extends Output<T>>	An immutable evaluation of a specific model and dataset.
interface	EvaluationRenderer<T extends Output<T>,E extends Evaluation<T>>	Renders an Evaluation into a String.
interface	Evaluator<T extends Output<T>,E extends Evaluation<T>>	An evaluation factory which produces immutable Evaluations of a given Dataset using the given Model.
class	KFoldSplitter<T extends Output<T>>	A k-fold splitter to be used in cross-validation.
static class	KFoldSplitter.TrainTestFold<T extends Output<T>>	Stores a train/test split for a dataset.
final class	OnlineEvaluator<T extends Output<T>,E extends Evaluation<T>>	An evaluator which aggregates predictions and produces Evaluations covering all the Predictions it has seen or created.
class	TrainTestSplitter<T extends Output<T>>	Splits data into training and testing sets.

Methods in org.tribuo.evaluation with type parameters of type Output

Modifier and Type	Method	Description
static <T extends Output<T>, R extends Evaluation<T>> com.oracle.labs.mlrg.olcut.util.Pair<Integer,Double>	EvaluationAggregator.argmax(List<R> evaluations, Function<R,Double> getter)	Calculates the argmax of a metric across the supplied evaluations.
static <T extends Output<T>, C extends MetricContext<T>> com.oracle.labs.mlrg.olcut.util.Pair<Integer,Double>	EvaluationAggregator.argmax(EvaluationMetric<T,C> metric, List<? extends Model<T>> models, Dataset<T> dataset)	Calculates the argmax of a metric across the supplied models (i.e., the index of the model which performed the best).
static <T extends Output<T>, C extends MetricContext<T>> com.oracle.labs.mlrg.olcut.util.Pair<Integer,Double>	EvaluationAggregator.argmax(EvaluationMetric<T,C> metric, Model<T> model, List<? extends Dataset<T>> datasets)	Calculates the argmax of a metric across the supplied datasets.
static <T extends Output<T>, C extends MetricContext<T>> DescriptiveStats	EvaluationAggregator.summarize(List<? extends EvaluationMetric<T,C>> metrics, Model<T> model, List<Prediction<T>> predictions)	Summarize model performance on dataset across several metrics.
static <T extends Output<T>, C extends MetricContext<T>> DescriptiveStats	EvaluationAggregator.summarize(List<? extends EvaluationMetric<T,C>> metrics, Model<T> model, Dataset<T> dataset)	Summarize model performance on dataset across several metrics.
static <T extends Output<T>, R extends Evaluation<T>> Map<MetricID<T>,DescriptiveStats>	EvaluationAggregator.summarize(List<R> evaluations)	Summarize all fields of a list of evaluations.
static <T extends Output<T>, R extends Evaluation<T>> DescriptiveStats	EvaluationAggregator.summarize(List<R> evaluations, ToDoubleFunction<R> fieldGetter)	Summarize a single field of an evaluation across several evaluations.
static <T extends Output<T>, R extends Evaluation<T>> Map<MetricID<T>,DescriptiveStats>	EvaluationAggregator.summarize(Evaluator<T,R> evaluator, List<? extends Model<T>> models, Dataset<T> dataset)	Summarize performance using the supplied evaluator across several models on one dataset.
static <T extends Output<T>, R extends Evaluation<T>> Map<MetricID<T>,DescriptiveStats>	EvaluationAggregator.summarize(Evaluator<T,R> evaluator, Model<T> model, List<? extends Dataset<T>> datasets)	Summarize performance according to evaluator for a single model across several datasets.
static <T extends Output<T>, C extends MetricContext<T>> DescriptiveStats	EvaluationAggregator.summarize(EvaluationMetric<T,C> metric, List<? extends Model<T>> models, Dataset<T> dataset)	Summarize performance w.r.t.
static <T extends Output<T>, C extends MetricContext<T>> DescriptiveStats	EvaluationAggregator.summarize(EvaluationMetric<T,C> metric, Model<T> model, List<? extends Dataset<T>> datasets)	Summarize a model's performance w.r.t.

Uses of Output in org.tribuo.evaluation.metrics

Classes in org.tribuo.evaluation.metrics with type parameters of type Output

Modifier and Type	Interface	Description
interface	EvaluationMetric<T extends Output<T>,C extends MetricContext<T>>	A metric that can be calculated for the specified output type.
class	MetricContext<T extends Output<T>>	The context for a metric or set of metrics.
final class	MetricID<T extends Output<T>>	Just an easier-to-read alias for Pair<MetricTarget<T>, String>.
class	MetricTarget<T extends Output<T>>	Used by a given EvaluationMetric to determine whether it should compute its value for a specific Output value or whether it should average them.

Methods in org.tribuo.evaluation.metrics with type parameters of type Output

Modifier and Type	Method	Description
static <U extends Output<U>> MetricTarget<U>	MetricTarget.macroAverageTarget()	Get the singleton MetricTarget which contains the EvaluationMetric.Average.MACRO.
static <U extends Output<U>> MetricTarget<U>	MetricTarget.microAverageTarget()	Get the singleton MetricTarget which contains the EvaluationMetric.Average.MICRO.

Uses of Output in org.tribuo.hash

Classes in org.tribuo.hash with type parameters of type Output

Modifier and Type	Class	Description
final class	HashingTrainer<T extends Output<T>>	A Trainer which hashes the Dataset before the Model is produced.

Methods in org.tribuo.hash with type parameters of type Output

Modifier and Type	Method	Description
<T extends Output<T>> Trainer<T>	HashingOptions.getHashedTrainer(Trainer<T> innerTrainer)	Gets the trainer wrapped in a hashing trainer.

Uses of Output in org.tribuo.impl

Classes in org.tribuo.impl with type parameters of type Output

Modifier and Type	Class	Description
class	ArrayExample<T extends Output<T>>	An Example backed by two arrays, one of String and one of double.
final class	BinaryFeaturesExample<T extends Output<T>>	An Example backed by a single array of feature names.
class	IndexedArrayExample<T extends Output<T>>	A version of ArrayExample which also has the id numbers.
class	ListExample<T extends Output<T>>	This class will not be performant until value types are available in Java.

Uses of Output in org.tribuo.interop

Classes in org.tribuo.interop with type parameters of type Output

Modifier and Type	Class	Description
class	ExternalModel<T extends Output<T>,U,V>	This is the base class for third party models which are trained externally and loaded into Tribuo for prediction.

Methods in org.tribuo.interop with type parameters of type Output

Modifier and Type	Method	Description
protected static <T extends Output<T>> ImmutableOutputInfo<T>	ExternalModel.createOutputInfo(OutputFactory<T> factory, Map<T,Integer> outputs)	Creates an output info from a set of outputs.

Uses of Output in org.tribuo.interop.oci

Classes in org.tribuo.interop.oci with type parameters of type Output

Modifier and Type	Class	Description
final class	OCIModel<T extends Output<T>>	A wrapper class around an OCI Data Science Model Deployment endpoint which sends off inputs for scoring and converts the output into a Tribuo prediction.
interface	OCIOutputConverter<T extends Output<T>>	Converter for a DenseMatrix received from OCI Data Science Model Deployment.

Methods in org.tribuo.interop.oci with type parameters of type Output

Modifier and Type	Method	Description
static <T extends Output<T>, U extends Model<T> & ONNXExportable> String	OCIUtil.createModel(U model, com.oracle.bmc.datascience.DataScienceClient client, com.fasterxml.jackson.databind.ObjectMapper mapper, OCIUtil.OCIModelArtifactConfig config)	Creates an OCI DS model and uploads the model artifact.
static <T extends Output<T>> OCIModel<T>	OCIModel.createOCIModel(OutputFactory<T> factory, Map<String,Integer> featureMapping, Map<T,Integer> outputMapping, Path configFile, String profileName, String endpointURL, OCIOutputConverter<T> outputConverter)	Creates an OCIModel by wrapping an OCI DS Model Deployment endpoint.
static <T extends Output<T>> OCIModel<T>	OCIModel.createOCIModel(OutputFactory<T> factory, Map<String,Integer> featureMapping, Map<T,Integer> outputMapping, Path configFile, String endpointURL, OCIOutputConverter<T> outputConverter)	Creates an OCIModel by wrapping an OCI DS Model Deployment endpoint.

Uses of Output in org.tribuo.interop.onnx

Classes in org.tribuo.interop.onnx with type parameters of type Output

Modifier and Type	Class	Description
final class	ONNXExternalModel<T extends Output<T>>	A Tribuo wrapper around a ONNX model.
interface	OutputTransformer<T extends Output<T>>	Converts an OnnxValue into an Output or a Prediction.

Methods in org.tribuo.interop.onnx with type parameters of type Output

Modifier and Type	Method	Description
static <T extends Output<T>> ONNXExternalModel<T>	ONNXExternalModel.createOnnxModel(OutputFactory<T> factory, Map<String,Integer> featureMapping, Map<T,Integer> outputMapping, ExampleTransformer featureTransformer, OutputTransformer<T> outputTransformer, ai.onnxruntime.OrtSession.SessionOptions opts, String filename, String inputName)	Creates an ONNXExternalModel by loading the model from disk.
static <T extends Output<T>> ONNXExternalModel<T>	ONNXExternalModel.createOnnxModel(OutputFactory<T> factory, Map<String,Integer> featureMapping, Map<T,Integer> outputMapping, ExampleTransformer featureTransformer, OutputTransformer<T> outputTransformer, ai.onnxruntime.OrtSession.SessionOptions opts, Path path, String inputName)	Creates an ONNXExternalModel by loading the model from disk.

Uses of Output in org.tribuo.interop.onnx.extractors

Classes in org.tribuo.interop.onnx.extractors with type parameters of type Output

Modifier and Type	Class	Description
class	BERTFeatureExtractor<T extends Output<T>>	Builds examples and sequence examples using features from BERT.

Uses of Output in org.tribuo.interop.tensorflow

Classes in org.tribuo.interop.tensorflow with type parameters of type Output

Modifier and Type	Interface	Description
interface	OutputConverter<T extends Output<T>>	Converts the Output into a Tensor and vice versa.
final class	TensorFlowCheckpointModel<T extends Output<T>>	This model encapsulates a simple model with an input feed dict, and produces a single output tensor.
final class	TensorFlowFrozenExternalModel<T extends Output<T>>	A Tribuo wrapper around a TensorFlow frozen model.
class	TensorFlowModel<T extends Output<T>>	Base class for a TensorFlow model that operates on Examples.
final class	TensorFlowNativeModel<T extends Output<T>>	This model encapsulates a TensorFlow model running in graph mode with a single tensor output.
final class	TensorFlowSavedModelExternalModel<T extends Output<T>>	A Tribuo wrapper around a TensorFlow saved model bundle.
final class	TensorFlowTrainer<T extends Output<T>>	Trainer for TensorFlow.

Methods in org.tribuo.interop.tensorflow with type parameters of type Output

Modifier and Type	Method	Description
static <T extends Output<T>> TensorFlowFrozenExternalModel<T>	TensorFlowFrozenExternalModel.createTensorflowModel(OutputFactory<T> factory, Map<String,Integer> featureMapping, Map<T,Integer> outputMapping, String inputName, String outputName, FeatureConverter featureConverter, OutputConverter<T> outputConverter, String filename)	Creates a TensorflowFrozenExternalModel by loading in a frozen graph.
static <T extends Output<T>> TensorFlowSavedModelExternalModel<T>	TensorFlowSavedModelExternalModel.createTensorflowModel(OutputFactory<T> factory, Map<String,Integer> featureMapping, Map<T,Integer> outputMapping, String outputName, FeatureConverter featureConverter, OutputConverter<T> outputConverter, String bundleDirectory)	Creates a TensorflowSavedModelExternalModel by loading in a SavedModelBundle.

Uses of Output in org.tribuo.interop.tensorflow.sequence

Classes in org.tribuo.interop.tensorflow.sequence with type parameters of type Output

Modifier and Type	Interface	Description
interface	SequenceOutputConverter<T extends Output<T>>	Converts a TensorFlow output tensor into a list of predictions, and a Tribuo sequence example into a Tensorflow tensor suitable for training.
class	TensorFlowSequenceModel<T extends Output<T>>	A TensorFlow model which implements SequenceModel, suitable for use in sequential prediction tasks.
class	TensorFlowSequenceTrainer<T extends Output<T>>	A trainer for SequenceModels which use an underlying TensorFlow graph.

Uses of Output in org.tribuo.json

Classes in org.tribuo.json with type parameters of type Output

Modifier and Type	Class	Description
class	JsonDataSource<T extends Output<T>>	A DataSource for loading data from a JSON text file and applying FieldProcessors to it.

Methods in org.tribuo.json with type parameters of type Output

Modifier and Type	Method	Description
static <T extends Output<T>> void	StripProvenance.main(String[] args)	Runs StripProvenance.

Uses of Output in org.tribuo.math.la

Methods in org.tribuo.math.la with type parameters of type Output

Modifier and Type	Method	Description
static <T extends Output<T>> DenseVector	DenseVector.createDenseVector(Example<T> example, ImmutableFeatureMap featureInfo, boolean addBias)	Builds a DenseVector from an Example.
static <T extends Output<T>> SparseVector	SparseVector.createSparseVector(Example<T> example, ImmutableFeatureMap featureInfo, boolean addBias)	Builds a SparseVector from an Example.
static <T extends Output<T>> SparseVector[]	SparseVector.transpose(Dataset<T> dataset)	Converts a dataset of row-major examples into an array of column-major sparse vectors.
static <T extends Output<T>> SparseVector[]	SparseVector.transpose(Dataset<T> dataset, ImmutableFeatureMap fMap)	Converts a dataset of row-major examples into an array of column-major sparse vectors.

Uses of Output in org.tribuo.multilabel

Classes in org.tribuo.multilabel that implement Output

Modifier and Type	Class	Description
class	MultiLabel	A class for multi-label classification.

Uses of Output in org.tribuo.regression

Classes in org.tribuo.regression that implement Output

Modifier and Type	Class	Description
class	Regressor	An Output for n-dimensional real valued regression.
static final class	Regressor.DimensionTuple	A Regressor which contains a single dimension, used internally when the model implementation doesn't natively support multi-dimensional regression outputs.

Uses of Output in org.tribuo.reproducibility

Classes in org.tribuo.reproducibility with type parameters of type Output

Modifier and Type	Class	Description
final class	ReproUtil<T extends Output<T>>	Reproducibility utility based on Tribuo's provenance objects.
static final record	ReproUtil.ModelReproduction<T extends Output<T>>	Record for a model reproduction.
static final record	ReproUtil.OutputDiff<T extends Output<T>>	Record for any differences between output domains.

Uses of Output in org.tribuo.sequence

Classes in org.tribuo.sequence with type parameters of type Output

Modifier and Type	Class	Description
class	AbstractSequenceEvaluator<T extends Output<T>,C extends MetricContext<T>,E extends SequenceEvaluation<T>,M extends EvaluationMetric<T,C>>	Base class for sequence evaluators.
final class	HashingSequenceTrainer<T extends Output<T>>	A SequenceTrainer that hashes all the feature names on the way in.
class	ImmutableSequenceDataset<T extends Output<T>>	This is a SequenceDataset which has an ImmutableFeatureMap to store the feature information.
class	IndependentSequenceModel<T extends Output<T>>	A SequenceModel which independently predicts each element of the sequence.
class	IndependentSequenceTrainer<T extends Output<T>>	Trains a sequence model by training a regular model to independently predict every example in each sequence.
class	MinimumCardinalitySequenceDataset<T extends Output<T>>	This class creates a pruned dataset in which low frequency features that occur less than the provided minimum cardinality have been removed.
class	MutableSequenceDataset<T extends Output<T>>	A MutableSequenceDataset is a SequenceDataset with a MutableFeatureMap which grows over time.
class	SequenceDataset<T extends Output<T>>	A class for sets of data, which are used to train and evaluate classifiers.
interface	SequenceDataSource<T extends Output<T>>	A interface for things that can be given to a SequenceDataset's constructor.
interface	SequenceEvaluation<T extends Output<T>>	An immutable evaluation of a specific sequence model and dataset.
interface	SequenceEvaluator<T extends Output<T>,E extends SequenceEvaluation<T>>	An evaluation factory which produces immutable SequenceEvaluations of a given SequenceDataset using the given SequenceModel.
class	SequenceExample<T extends Output<T>>	A sequence of examples, used for sequence classification.
class	SequenceModel<T extends Output<T>>	A prediction model, which is used to predict outputs for unseen instances.
interface	SequenceTrainer<T extends Output<T>>	An interface for things that can train sequence prediction models.

Methods in org.tribuo.sequence with type parameters of type Output

Modifier and Type	Method	Description
static <T extends Output<T>> ImmutableSequenceDataset<T>	ImmutableSequenceDataset.copyDataset(SequenceDataset<T> dataset)	Creates an immutable deep copy of the supplied dataset.
static <T extends Output<T>> ImmutableSequenceDataset<T>	ImmutableSequenceDataset.copyDataset(SequenceDataset<T> dataset, ImmutableFeatureMap featureIDMap, ImmutableOutputInfo<T> outputIDInfo)	Creates an immutable deep copy of the supplied dataset, using a different feature and output map.
static <T extends Output<T>> ImmutableSequenceDataset<T>	ImmutableSequenceDataset.copyDataset(SequenceDataset<T> dataset, ImmutableFeatureMap featureIDMap, ImmutableOutputInfo<T> outputIDInfo, Merger merger)	Creates an immutable deep copy of the supplied dataset.
static <T extends Output<T>> SequenceExample<T>	SequenceExample.createWithEmptyOutputs(List<? extends List<? extends Feature>> features, OutputFactory<T> outputFactory)	Creates a SequenceExample using OutputFactory.getUnknownOutput() as the output for each sequence element.
static <T extends Output<T>> List<T>	SequenceModel.toMaxLabels(List<Prediction<T>> predictions)	Extracts a list of the predicted outputs from the list of prediction objects.

Method parameters in org.tribuo.sequence with type arguments of type Output

Modifier and Type	Method	Description
boolean	SequenceModel.validate(Class<? extends Output<?>> clazz)	Validates that this Model does in fact support the supplied output type.

Uses of Output in org.tribuo.transform

Classes in org.tribuo.transform with type parameters of type Output

Modifier and Type	Class	Description
class	TransformedModel<T extends Output<T>>	Wraps a Model with it's TransformerMap so all Examples are transformed appropriately before the model makes predictions.
final class	TransformTrainer<T extends Output<T>>	A Trainer which encapsulates another trainer plus a TransformationMap object to apply to each Dataset before training each Model.

Methods in org.tribuo.transform with type parameters of type Output

Modifier and Type	Method	Description
<T extends Output<T>> MutableDataset<T>	TransformerMap.transformDataset(Dataset<T> dataset)	Copies the supplied dataset and applies the transformers to each example in it.
<T extends Output<T>> MutableDataset<T>	TransformerMap.transformDataset(Dataset<T> dataset, boolean densify)	Copies the supplied dataset and applies the transformers to each example in it.
<T extends Output<T>> Example<T>	TransformerMap.transformExample(Example<T> example)	Copies the supplied example and applies the transformers to it.
<T extends Output<T>> Example<T>	TransformerMap.transformExample(Example<T> example, List<String> featureNames)	Copies the supplied example and applies the transformers to it.