Uses of Class
org.tribuo.Example

Packages that use Example

Package	Description
org.tribuo	Provides the core interfaces and classes for using Tribuo.
org.tribuo.anomaly.example	Provides a anomaly data generator used for testing implementations.
org.tribuo.anomaly.liblinear	Provides an interface to LibLinear-java for anomaly detection problems.
org.tribuo.anomaly.libsvm	Provides an interface to LibSVM for anomaly detection problems.
org.tribuo.classification.baseline	Provides simple baseline multiclass classifiers.
org.tribuo.classification.example	Provides a multiclass data generator used for testing implementations.
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.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.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.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.columnar	Provides classes for processing columnar data and generating Examples.
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.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.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.math.la	Provides a linear algebra system used for numerical operations in Tribuo.
org.tribuo.multilabel.baseline	Provides an implementation of independent multi-label classification that wraps a Label Trainer and uses it to make independent predictions of each label.
org.tribuo.multilabel.example	Provides a multi-label data generator for testing implementations.
org.tribuo.multilabel.sgd.linear	Provides an implementation of a multi-label classification linear model using Stochastic Gradient Descent.
org.tribuo.regression.baseline	Provides simple baseline regression predictors.
org.tribuo.regression.example	Provides some example regression data generators for testing implementations.
org.tribuo.regression.impl	Provides skeletal implementations of Regressor Trainer that can wrap a single dimension trainer/model and produce one prediction per dimension independently.
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.sgd.linear	Provides an implementation of linear regression using Stochastic Gradient Descent.
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 Examples.
org.tribuo.transform	Provides infrastructure for applying transformations to a Dataset.

Uses of Example in org.tribuo

Fields in org.tribuo with type parameters of type Example

Modifier and Type	Field and Description
protected List<Example<T>>	Dataset.data The data in this data set.

Methods in org.tribuo that return Example

Modifier and Type	Method and Description
abstract Example<T>	Example.copy() Returns a deep copy of this Example.
Example<T>	Prediction.getExample() Returns the example itself.
Example<T>	Excuse.getExample() The example being excused.
Example<T>	Dataset.getExample(int index) Gets the example at the supplied index.

Methods in org.tribuo that return types with arguments of type Example

Modifier and Type	Method and Description
List<Example<T>>	Dataset.getData() Gets the examples as an unmodifiable list.
Iterator<Example<T>>	Dataset.iterator()

Methods in org.tribuo with parameters of type Example

Modifier and Type	Method and Description
void	MutableDataset.add(Example<T> ex) Adds an example to the dataset, which observes the output and each feature value.
protected void	ImmutableDataset.add(Example<T> ex) Adds an Example to the dataset, which will remove features with unknown names.
protected void	ImmutableDataset.add(Example<T> ex, Merger merger) Adds a Example to the dataset, which will insert feature ids, remove unknown features and sort the examples by the feature ids (merging duplicate ids).
abstract Optional<Excuse<T>>	Model.getExcuse(Example<T> example) Generates an excuse for an example.
abstract Prediction<T>	Model.predict(Example<T> example) Uses the model to predict the output for a single example.

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

Modifier and Type	Method and Description
void	MutableDataset.addAll(Collection<? extends Example<T>> collection) Adds all the Examples in the supplied collection to this dataset.
Optional<List<Excuse<T>>>	Model.getExcuses(Iterable<Example<T>> examples) Generates an excuse for each example.
protected List<Prediction<T>>	Model.innerPredict(Iterable<Example<T>> examples) Called by the base implementations of Model.predict(Iterable) and Model.predict(Dataset).
List<Prediction<T>>	Model.predict(Iterable<Example<T>> examples) Uses the model to predict the output for multiple examples.

Constructors in org.tribuo with parameters of type Example

Constructor and Description
Example(Example<T> other) Copies the output, weight and metadata into this example.
Excuse(Example<T> example, Prediction<T> prediction, Map<String,List<com.oracle.labs.mlrg.olcut.util.Pair<String,Double>>> weights) Constructs an excuse for the prediction of the supplied example, using the feature weights.
Prediction(Prediction<T> other, int numUsed, Example<T> example) Constructs a prediction from the supplied arguments.
Prediction(T output, int numUsed, Example<T> example) Constructs a prediction from the supplied arguments.
Prediction(T output, Map<String,T> outputScores, int numUsed, Example<T> example, boolean probability) Constructs a prediction from the supplied arguments.

Constructor parameters in org.tribuo with type arguments of type Example

Constructor and Description
ImmutableDataset(Iterable<Example<T>> dataSource, DataProvenance description, OutputFactory<T> outputFactory, FeatureMap featureIDMap, OutputInfo<T> outputIDInfo, boolean dropInvalidExamples) Creates a dataset from a data source.
ImmutableDataset(Iterable<Example<T>> dataSource, DataProvenance description, OutputFactory<T> outputFactory, ImmutableFeatureMap featureIDMap, ImmutableOutputInfo<T> outputIDInfo, boolean dropInvalidExamples) Creates a dataset from a data source.
MutableDataset(Iterable<Example<T>> dataSource, DataProvenance provenance, OutputFactory<T> outputFactory) Creates a dataset from a data source.

Uses of Example in org.tribuo.anomaly.example

Methods in org.tribuo.anomaly.example that return Example

Modifier and Type	Method and Description
static Example<Event>	AnomalyDataGenerator.emptyExample() Generates an example with no features.
static Example<Event>	AnomalyDataGenerator.invalidSparseExample() Generates an example with the feature ids 1,5,8, which does not intersect with the ids used elsewhere in this class.

Uses of Example in org.tribuo.anomaly.liblinear

Methods in org.tribuo.anomaly.liblinear with parameters of type Example

Modifier and Type	Method and Description
protected Excuse<Event>	LibLinearAnomalyModel.innerGetExcuse(Example<Event> e, double[][] allFeatureWeights) The call to model.getFeatureWeights in the public methods copies the weights array so this inner method exists to save the copy in getExcuses.
Prediction<Event>	LibLinearAnomalyModel.predict(Example<Event> example)

Uses of Example in org.tribuo.anomaly.libsvm

Methods in org.tribuo.anomaly.libsvm with parameters of type Example

Modifier and Type	Method and Description
Prediction<Event>	LibSVMAnomalyModel.predict(Example<Event> example)

Uses of Example in org.tribuo.classification.baseline

Methods in org.tribuo.classification.baseline with parameters of type Example

Modifier and Type	Method and Description
Optional<Excuse<Label>>	DummyClassifierModel.getExcuse(Example<Label> example)
Prediction<Label>	DummyClassifierModel.predict(Example<Label> example)

Uses of Example in org.tribuo.classification.example

Methods in org.tribuo.classification.example that return Example

Modifier and Type	Method and Description
static Example<Label>	LabelledDataGenerator.emptyExample() Generates an example with no features.
static Example<Label>	LabelledDataGenerator.invalidSparseExample() Generates an example with the feature ids 1,5,8, which does not intersect with the ids used elsewhere in this class.

Uses of Example in org.tribuo.classification.explanations

Methods in org.tribuo.classification.explanations with parameters of type Example

Modifier and Type	Method and Description
Explanation<T>	TabularExplainer.explain(Example<Label> example) Explain why the supplied Example is classified a certain way.

Uses of Example in org.tribuo.classification.explanations.lime

Methods in org.tribuo.classification.explanations.lime that return Example

Modifier and Type	Method and Description
static Example<Label>	LIMEBase.samplePoint(Random rng, ImmutableFeatureMap fMap, long numTrainingExamples, SparseVector input) Samples a single example from the supplied feature map and input vector.

Methods in org.tribuo.classification.explanations.lime that return types with arguments of type Example

Modifier and Type	Method and Description
protected com.oracle.labs.mlrg.olcut.util.Pair<LIMEExplanation,List<Example<Regressor>>>	LIMEBase.explainWithSamples(Example<Label> example)
protected com.oracle.labs.mlrg.olcut.util.Pair<LIMEExplanation,List<Example<Regressor>>>	LIMEColumnar.explainWithSamples(Map<String,String> input)
protected List<Example<Regressor>>	LIMEText.sampleData(String inputText, List<Token> tokens) Samples a new dataset from the input text.

Methods in org.tribuo.classification.explanations.lime with parameters of type Example

Modifier and Type	Method and Description
LIMEExplanation	LIMEBase.explain(Example<Label> example)
protected com.oracle.labs.mlrg.olcut.util.Pair<LIMEExplanation,List<Example<Regressor>>>	LIMEBase.explainWithSamples(Example<Label> example)
protected SparseModel<Regressor>	LIMEBase.trainExplainer(Example<Regressor> target, List<Example<Regressor>> samples) Trains the explanation model using the supplied sampled data and the input example.

Method parameters in org.tribuo.classification.explanations.lime with type arguments of type Example

Modifier and Type	Method and Description
protected SparseModel<Regressor>	LIMEBase.trainExplainer(Example<Regressor> target, List<Example<Regressor>> samples) Trains the explanation model using the supplied sampled data and the input example.

Uses of Example in org.tribuo.classification.liblinear

Methods in org.tribuo.classification.liblinear with parameters of type Example

Modifier and Type	Method and Description
protected Excuse<Label>	LibLinearClassificationModel.innerGetExcuse(Example<Label> e, double[][] allFeatureWeights) The call to model.getFeatureWeights in the public methods copies the weights array so this inner method exists to save the copy in getExcuses.
Prediction<Label>	LibLinearClassificationModel.predict(Example<Label> example)

Uses of Example in org.tribuo.classification.libsvm

Methods in org.tribuo.classification.libsvm with parameters of type Example

Modifier and Type	Method and Description
Prediction<Label>	LibSVMClassificationModel.predict(Example<Label> example)

Uses of Example in org.tribuo.classification.mnb

Methods in org.tribuo.classification.mnb with parameters of type Example

Modifier and Type	Method and Description
Optional<Excuse<Label>>	MultinomialNaiveBayesModel.getExcuse(Example<Label> example)
Prediction<Label>	MultinomialNaiveBayesModel.predict(Example<Label> example)

Uses of Example in org.tribuo.classification.sgd.kernel

Methods in org.tribuo.classification.sgd.kernel with parameters of type Example

Modifier and Type	Method and Description
Optional<Excuse<Label>>	KernelSVMModel.getExcuse(Example<Label> example)
Prediction<Label>	KernelSVMModel.predict(Example<Label> example)

Uses of Example in org.tribuo.classification.sgd.linear

Methods in org.tribuo.classification.sgd.linear with parameters of type Example

Modifier and Type	Method and Description
Prediction<Label>	LinearSGDModel.predict(Example<Label> example)

Uses of Example in org.tribuo.classification.xgboost

Methods in org.tribuo.classification.xgboost with parameters of type Example

Modifier and Type	Method and Description
List<Prediction<Label>>	XGBoostClassificationConverter.convertBatchOutput(ImmutableOutputInfo<Label> info, List<float[][]> probabilitiesList, int[] numValidFeatures, Example<Label>[] examples)
Prediction<Label>	XGBoostClassificationConverter.convertOutput(ImmutableOutputInfo<Label> info, List<float[]> probabilitiesList, int numValidFeatures, Example<Label> example)

Uses of Example in org.tribuo.clustering.example

Methods in org.tribuo.clustering.example that return Example

Modifier and Type	Method and Description
static Example<ClusterID>	ClusteringDataGenerator.emptyExample() Generates an example with no features.
static Example<ClusterID>	ClusteringDataGenerator.invalidSparseExample() Generates an example with the feature ids 1,5,8, which does not intersect with the ids used elsewhere in this class.

Uses of Example in org.tribuo.clustering.kmeans

Methods in org.tribuo.clustering.kmeans with parameters of type Example

Modifier and Type	Method and Description
Optional<Excuse<ClusterID>>	KMeansModel.getExcuse(Example<ClusterID> example)
Prediction<ClusterID>	KMeansModel.predict(Example<ClusterID> example)

Uses of Example in org.tribuo.common.liblinear

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

Modifier and Type	Method and 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.
Optional<Excuse<T>>	LibLinearModel.getExcuse(Example<T> e) This call is expensive as it copies out the weight matrix from the LibLinear model.
protected abstract Excuse<T>	LibLinearModel.innerGetExcuse(Example<T> e, double[][] featureWeights) The call to getFeatureWeights in the public methods copies the weights array so this inner method exists to save the copy in getExcuses.

Method parameters in org.tribuo.common.liblinear with type arguments of type Example

Modifier and Type	Method and Description
Optional<List<Excuse<T>>>	LibLinearModel.getExcuses(Iterable<Example<T>> examples)

Uses of Example in org.tribuo.common.libsvm

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

Modifier and Type	Method and 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.
Optional<Excuse<T>>	LibSVMModel.getExcuse(Example<T> example)

Uses of Example in org.tribuo.common.nearest

Methods in org.tribuo.common.nearest with parameters of type Example

Modifier and Type	Method and Description
Optional<Excuse<T>>	KNNModel.getExcuse(Example<T> example)
Prediction<T>	KNNModel.predict(Example<T> example)

Method parameters in org.tribuo.common.nearest with type arguments of type Example

Modifier and Type	Method and Description
protected List<Prediction<T>>	KNNModel.innerPredict(Iterable<Example<T>> examples) Uses the model to predict the output for multiple examples.

Uses of Example in org.tribuo.common.sgd

Methods in org.tribuo.common.sgd with parameters of type Example

Modifier and Type	Method and Description
Optional<Excuse<T>>	AbstractLinearSGDModel.getExcuse(Example<T> example)
protected AbstractSGDModel.PredAndActive	AbstractSGDModel.predictSingle(Example<T> example) Generates the dense vector prediction from the supplied example.

Uses of Example in org.tribuo.common.tree

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

Modifier and Type	Method and Description
Optional<Excuse<T>>	TreeModel.getExcuse(Example<T> example)
Prediction<T>	LeafNode.getPrediction(int numUsed, Example<T> example) Constructs a new prediction object based on this node's scores.
Prediction<T>	TreeModel.predict(Example<T> example)

Uses of Example in org.tribuo.common.xgboost

Fields in org.tribuo.common.xgboost declared as Example

Modifier and Type	Field and Description
Example<T>[]	XGBoostTrainer.DMatrixTuple.examples

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

Modifier and Type	Method and Description
List<Prediction<T>>	XGBoostOutputConverter.convertBatchOutput(ImmutableOutputInfo<T> info, List<float[][]> probabilities, int[] numValidFeatures, Example<T>[] examples) Converts a list of float arrays from XGBoost Boosters into a Tribuo Prediction.
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 Prediction<T>	XGBoostExternalModel.convertOutput(float[][] output, int numValidFeatures, Example<T> example)
Prediction<T>	XGBoostOutputConverter.convertOutput(ImmutableOutputInfo<T> info, List<float[]> probabilities, int numValidFeatures, Example<T> example) Converts a list of float arrays from XGBoost Boosters into a Tribuo Prediction.
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.
Optional<Excuse<T>>	XGBoostModel.getExcuse(Example<T> example)
Prediction<T>	XGBoostModel.predict(Example<T> example)

Method parameters in org.tribuo.common.xgboost with type arguments of type Example

Modifier and Type	Method and Description
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 List<Prediction<T>>	XGBoostExternalModel.convertOutput(float[][] output, int[] numValidFeatures, List<Example<T>> examples)
List<Prediction<T>>	XGBoostModel.predict(Iterable<Example<T>> examples) Uses the model to predict the label for multiple examples.

Constructors in org.tribuo.common.xgboost with parameters of type Example

Constructor and Description
DMatrixTuple(ml.dmlc.xgboost4j.java.DMatrix data, int[] numValidFeatures, Example<T>[] examples)

Uses of Example in org.tribuo.data.columnar

Methods in org.tribuo.data.columnar that return types with arguments of type Example

Modifier and Type	Method and Description
Optional<Example<T>>	RowProcessor.generateExample(ColumnarIterator.Row row, boolean outputRequired) Generate an Example from the supplied row.
Optional<Example<T>>	RowProcessor.generateExample(long idx, Map<String,String> row, boolean outputRequired) Generate an Example from the supplied row.
Optional<Example<T>>	RowProcessor.generateExample(Map<String,String> row, boolean outputRequired) Generate an Example from the supplied row.
Iterator<Example<T>>	ColumnarDataSource.iterator()

Uses of Example in org.tribuo.data.text

Fields in org.tribuo.data.text with type parameters of type Example

Modifier and Type	Field and Description
protected List<Example<T>>	TextDataSource.data The actual data read out of the text file.

Methods in org.tribuo.data.text that return Example

Modifier and Type	Method and Description
Example<T>	TextFeatureExtractor.extract(T output, String data) Extracts an example from the supplied input text and output object.

Methods in org.tribuo.data.text that return types with arguments of type Example

Modifier and Type	Method and Description
Iterator<Example<T>>	TextDataSource.iterator()
Iterator<Example<T>>	DirectoryFileSource.iterator()

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

Methods in org.tribuo.data.text.impl that return Example

Modifier and Type	Method and Description
Example<T>	TextFeatureExtractorImpl.extract(T label, String data)

Methods in org.tribuo.data.text.impl that return types with arguments of type Example

Modifier and Type	Method and Description
protected Optional<Example<T>>	SimpleTextDataSource.parseLine(String line, int n)

Uses of Example in org.tribuo.dataset

Methods in org.tribuo.dataset that return Example

Modifier and Type	Method and Description
Example<T>	DatasetView.getExample(int index)

Methods in org.tribuo.dataset that return types with arguments of type Example

Modifier and Type	Method and Description
List<Example<T>>	DatasetView.getData()
Iterator<Example<T>>	DatasetView.iterator()

Method parameters in org.tribuo.dataset with type arguments of type Example

Modifier and Type	Method and Description
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.

Uses of Example in org.tribuo.datasource

Methods in org.tribuo.datasource that return types with arguments of type Example

Modifier and Type	Method and Description
Iterator<Example<T>>	ListDataSource.iterator()
Iterator<Example<T>>	LibSVMDataSource.iterator()
Iterator<Example<T>>	IDXDataSource.iterator()
Iterator<Example<T>>	AggregateDataSource.iterator()
Iterator<Example<T>>	AggregateConfigurableDataSource.iterator()

Constructor parameters in org.tribuo.datasource with type arguments of type Example

Constructor and Description
ListDataSource(List<Example<T>> list, OutputFactory<T> factory, DataSourceProvenance provenance)

Uses of Example in org.tribuo.ensemble

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

Modifier and Type	Method and Description
Optional<Excuse<T>>	WeightedEnsembleModel.getExcuse(Example<T> example)
abstract Optional<Excuse<T>>	EnsembleModel.getExcuse(Example<T> example)
Prediction<T>	WeightedEnsembleModel.predict(Example<T> example)

Constructors in org.tribuo.ensemble with parameters of type Example

Constructor and Description
EnsembleExcuse(Example<T> example, Prediction<T> prediction, Map<String,List<com.oracle.labs.mlrg.olcut.util.Pair<String,Double>>> weights, List<Excuse<T>> innerExcuses)

Uses of Example in org.tribuo.evaluation

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

Modifier and Type	Method and Description
Prediction<T>	OnlineEvaluator.predictAndObserve(Example<T> example) Feeds the example to the model, records the prediction and returns it.

Method parameters in org.tribuo.evaluation with type arguments of type Example

Modifier and Type	Method and Description
List<Prediction<T>>	OnlineEvaluator.predictAndObserve(Iterable<Example<T>> examples) Feeds the examples to the model, records the predictions and returns them.

Uses of Example in org.tribuo.impl

Subclasses of Example in org.tribuo.impl

Modifier and Type	Class and Description
class	ArrayExample<T extends Output<T>> An Example backed by two arrays, one of String and one of double.
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.

Constructors in org.tribuo.impl with parameters of type Example

Constructor and Description
ArrayExample(Example<T> other) Copy constructor.
ArrayExample(T output, Example<U> other, float weight) Clones an example's features, but uses the supplied output and weight.
BinaryFeaturesExample(Example<T> other) Copy constructor.
BinaryFeaturesExample(T output, Example<U> other, float weight) Clones an example's features, but uses the supplied output and weight.
IndexedArrayExample(Example<T> other, ImmutableFeatureMap featureMap, ImmutableOutputInfo<T> outputMap) This constructor removes unknown features.
ListExample(Example<T> other)

Uses of Example in org.tribuo.interop

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

Modifier and Type	Method and Description
protected abstract Prediction<T>	ExternalModel.convertOutput(V output, int numValidFeatures, Example<T> example) Converts the output of the external model into a Prediction.
Optional<Excuse<T>>	ExternalModel.getExcuse(Example<T> example) By default third party models don't return excuses.
Prediction<T>	ExternalModel.predict(Example<T> example)

Method parameters in org.tribuo.interop with type arguments of type Example

Modifier and Type	Method and Description
protected abstract List<Prediction<T>>	ExternalModel.convertOutput(V output, int[] numValidFeatures, List<Example<T>> examples) Converts the output of the external model into a list of Predictions.
protected List<Prediction<T>>	ExternalModel.innerPredict(Iterable<Example<T>> examples)

Uses of Example in org.tribuo.interop.onnx

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

Modifier and Type	Method and Description
protected Prediction<T>	ONNXExternalModel.convertOutput(List<ai.onnxruntime.OnnxValue> output, int numValidFeatures, Example<T> example) Converts a tensor into a prediction.
Prediction<Label>	LabelTransformer.transformToPrediction(List<ai.onnxruntime.OnnxValue> tensor, ImmutableOutputInfo<Label> outputIDInfo, int numValidFeatures, Example<Label> example)
Prediction<Regressor>	RegressorTransformer.transformToPrediction(List<ai.onnxruntime.OnnxValue> tensor, ImmutableOutputInfo<Regressor> outputIDInfo, int numValidFeatures, Example<Regressor> example)
Prediction<T>	OutputTransformer.transformToPrediction(List<ai.onnxruntime.OnnxValue> value, ImmutableOutputInfo<T> outputIDInfo, int numValidFeatures, Example<T> example) Converts a OnnxValue into a Prediction.

Method parameters in org.tribuo.interop.onnx with type arguments of type Example

Modifier and Type	Method and Description
protected List<Prediction<T>>	ONNXExternalModel.convertOutput(List<ai.onnxruntime.OnnxValue> output, int[] numValidFeatures, List<Example<T>> examples) Converts a tensor into a prediction.
List<Prediction<Label>>	LabelTransformer.transformToBatchPrediction(List<ai.onnxruntime.OnnxValue> tensor, ImmutableOutputInfo<Label> outputIDInfo, int[] numValidFeatures, List<Example<Label>> examples)
List<Prediction<Regressor>>	RegressorTransformer.transformToBatchPrediction(List<ai.onnxruntime.OnnxValue> tensor, ImmutableOutputInfo<Regressor> outputIDInfo, int[] numValidFeatures, List<Example<Regressor>> examples)
List<Prediction<T>>	OutputTransformer.transformToBatchPrediction(List<ai.onnxruntime.OnnxValue> value, ImmutableOutputInfo<T> outputIDInfo, int[] numValidFeatures, List<Example<T>> examples) Converts a OnnxValue containing multiple outputs into a list of Predictions.

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

Methods in org.tribuo.interop.onnx.extractors that return Example

Modifier and Type	Method and Description
Example<T>	BERTFeatureExtractor.extract(T output, String data) Tokenizes the input using the loaded tokenizer, truncates the token list if it's longer than maxLength - 2 (to account for [CLS] and [SEP] tokens), and then passes the token list to BERTFeatureExtractor.extractExample(java.util.List<java.lang.String>).
Example<T>	BERTFeatureExtractor.extractExample(List<String> tokens) Passes the tokens through BERT, replacing any unknown tokens with the [UNK] token.
Example<T>	BERTFeatureExtractor.extractExample(List<String> tokens, T output) Passes the tokens through BERT, replacing any unknown tokens with the [UNK] token.

Uses of Example in org.tribuo.interop.tensorflow

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

Modifier and Type	Method and Description
TensorMap	ImageConverter.convert(Example<?> example, ImmutableFeatureMap featureIDMap) Transform implicitly pads unseen values with zero.
TensorMap	FeatureConverter.convert(Example<?> example, ImmutableFeatureMap featureIDMap) Converts an Example into a TensorMap suitable for supplying as an input to a graph.
TensorMap	DenseFeatureConverter.convert(Example<?> example, ImmutableFeatureMap featureIDMap)
protected Prediction<T>	TensorFlowFrozenExternalModel.convertOutput(org.tensorflow.Tensor output, int numValidFeatures, Example<T> example) Converts a tensor into a prediction.
protected Prediction<T>	TensorFlowSavedModelExternalModel.convertOutput(TensorMap output, int numValidFeatures, Example<T> example) Converts a tensor into a prediction.
Prediction<Label>	LabelConverter.convertToPrediction(org.tensorflow.Tensor tensor, ImmutableOutputInfo<Label> outputIDInfo, int numValidFeatures, Example<Label> example)
Prediction<MultiLabel>	MultiLabelConverter.convertToPrediction(org.tensorflow.Tensor tensor, ImmutableOutputInfo<MultiLabel> outputIDInfo, int numValidFeatures, Example<MultiLabel> example)
Prediction<Regressor>	RegressorConverter.convertToPrediction(org.tensorflow.Tensor tensor, ImmutableOutputInfo<Regressor> outputIDInfo, int numValidFeatures, Example<Regressor> example)
Prediction<T>	OutputConverter.convertToPrediction(org.tensorflow.Tensor tensor, ImmutableOutputInfo<T> outputIDInfo, int numValidFeatures, Example<T> example) Converts a Tensor into a Prediction.
Optional<Excuse<T>>	TensorFlowModel.getExcuse(Example<T> example) Deep learning models don't do excuses.
Prediction<T>	TensorFlowModel.predict(Example<T> example)

Method parameters in org.tribuo.interop.tensorflow with type arguments of type Example

Modifier and Type	Method and Description
TensorMap	ImageConverter.convert(List<? extends Example<?>> examples, ImmutableFeatureMap featureIDMap) Transform implicitly pads unseen values with zero.
TensorMap	FeatureConverter.convert(List<? extends Example<?>> example, ImmutableFeatureMap featureIDMap) Converts a batch of Examples into a single TensorMap suitable for supplying as an input to a graph.
TensorMap	DenseFeatureConverter.convert(List<? extends Example<?>> examples, ImmutableFeatureMap featureIDMap)
protected List<Prediction<T>>	TensorFlowFrozenExternalModel.convertOutput(org.tensorflow.Tensor output, int[] numValidFeatures, List<Example<T>> examples) Converts a tensor into a prediction.
protected List<Prediction<T>>	TensorFlowSavedModelExternalModel.convertOutput(TensorMap output, int[] numValidFeatures, List<Example<T>> examples) Converts a tensor into a prediction.
List<Prediction<Label>>	LabelConverter.convertToBatchPrediction(org.tensorflow.Tensor tensor, ImmutableOutputInfo<Label> outputIDInfo, int[] numValidFeatures, List<Example<Label>> examples)
List<Prediction<MultiLabel>>	MultiLabelConverter.convertToBatchPrediction(org.tensorflow.Tensor tensor, ImmutableOutputInfo<MultiLabel> outputIDInfo, int[] numValidFeatures, List<Example<MultiLabel>> examples)
List<Prediction<Regressor>>	RegressorConverter.convertToBatchPrediction(org.tensorflow.Tensor tensor, ImmutableOutputInfo<Regressor> outputIDInfo, int[] numValidFeatures, List<Example<Regressor>> examples)
List<Prediction<T>>	OutputConverter.convertToBatchPrediction(org.tensorflow.Tensor tensor, ImmutableOutputInfo<T> outputIDInfo, int[] numValidFeatures, List<Example<T>> examples) Converts a Tensor containing multiple outputs into a list of Predictions.
org.tensorflow.Tensor	LabelConverter.convertToTensor(List<Example<Label>> examples, ImmutableOutputInfo<Label> outputIDInfo)
org.tensorflow.Tensor	MultiLabelConverter.convertToTensor(List<Example<MultiLabel>> examples, ImmutableOutputInfo<MultiLabel> outputIDInfo)
org.tensorflow.Tensor	RegressorConverter.convertToTensor(List<Example<Regressor>> examples, ImmutableOutputInfo<Regressor> outputIDInfo)
org.tensorflow.Tensor	OutputConverter.convertToTensor(List<Example<T>> examples, ImmutableOutputInfo<T> outputIDInfo) Converts a list of Example into a Tensor representing all the outputs in the list.
protected List<Prediction<T>>	TensorFlowModel.innerPredict(Iterable<Example<T>> examples)

Uses of Example in org.tribuo.math.la

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

Modifier and Type	Method and 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.

Uses of Example in org.tribuo.multilabel.baseline

Methods in org.tribuo.multilabel.baseline with parameters of type Example

Modifier and Type	Method and Description
Optional<Excuse<MultiLabel>>	IndependentMultiLabelModel.getExcuse(Example<MultiLabel> example)
Prediction<MultiLabel>	IndependentMultiLabelModel.predict(Example<MultiLabel> example)

Uses of Example in org.tribuo.multilabel.example

Methods in org.tribuo.multilabel.example that return Example

Modifier and Type	Method and Description
static Example<MultiLabel>	MultiLabelDataGenerator.emptyExample() Generates an example with no features.
static Example<MultiLabel>	MultiLabelDataGenerator.invalidSparseExample() Generates an example with the feature ids 1,5,8, which does not intersect with the ids used elsewhere in this class.

Uses of Example in org.tribuo.multilabel.sgd.linear

Methods in org.tribuo.multilabel.sgd.linear with parameters of type Example

Modifier and Type	Method and Description
Prediction<MultiLabel>	LinearSGDModel.predict(Example<MultiLabel> example)

Uses of Example in org.tribuo.regression.baseline

Methods in org.tribuo.regression.baseline with parameters of type Example

Modifier and Type	Method and Description
Optional<Excuse<Regressor>>	DummyRegressionModel.getExcuse(Example<Regressor> example)
Prediction<Regressor>	DummyRegressionModel.predict(Example<Regressor> example)

Uses of Example in org.tribuo.regression.example

Methods in org.tribuo.regression.example that return Example

Modifier and Type	Method and Description
static Example<Regressor>	RegressionDataGenerator.emptyExample() Generates an example with no features.
static Example<Regressor>	RegressionDataGenerator.emptyMultiDimExample() Generates an example with no features.
static Example<Regressor>	RegressionDataGenerator.invalidMultiDimSparseExample() Generates an example with the feature ids 1,5,8, which does not intersect with the ids used elsewhere in this class.
static Example<Regressor>	RegressionDataGenerator.invalidSparseExample() Generates an example with the feature ids 1,5,8, which does not intersect with the ids used elsewhere in this class.

Methods in org.tribuo.regression.example that return types with arguments of type Example

Modifier and Type	Method and Description
Iterator<Example<Regressor>>	NonlinearGaussianDataSource.iterator()
Iterator<Example<Regressor>>	GaussianDataSource.iterator()

Uses of Example in org.tribuo.regression.impl

Methods in org.tribuo.regression.impl with parameters of type Example

Modifier and Type	Method and Description
protected SparseVector	SkeletalIndependentRegressionSparseModel.createFeatures(Example<Regressor> example) Creates the feature vector.
protected SparseVector	SkeletalIndependentRegressionModel.createFeatures(Example<Regressor> example) Creates the feature vector.
Prediction<Regressor>	SkeletalIndependentRegressionSparseModel.predict(Example<Regressor> example)
Prediction<Regressor>	SkeletalIndependentRegressionModel.predict(Example<Regressor> example)

Uses of Example in org.tribuo.regression.liblinear

Methods in org.tribuo.regression.liblinear with parameters of type Example

Modifier and Type	Method and Description
protected Excuse<Regressor>	LibLinearRegressionModel.innerGetExcuse(Example<Regressor> e, double[][] allFeatureWeights) The call to model.getFeatureWeights in the public methods copies the weights array so this inner method exists to save the copy in getExcuses.
Prediction<Regressor>	LibLinearRegressionModel.predict(Example<Regressor> example)

Uses of Example in org.tribuo.regression.libsvm

Methods in org.tribuo.regression.libsvm with parameters of type Example

Modifier and Type	Method and Description
Prediction<Regressor>	LibSVMRegressionModel.predict(Example<Regressor> example)

Uses of Example in org.tribuo.regression.rtree

Methods in org.tribuo.regression.rtree with parameters of type Example

Modifier and Type	Method and Description
Optional<Excuse<Regressor>>	IndependentRegressionTreeModel.getExcuse(Example<Regressor> example)
Prediction<Regressor>	IndependentRegressionTreeModel.predict(Example<Regressor> example)

Uses of Example in org.tribuo.regression.sgd.linear

Methods in org.tribuo.regression.sgd.linear with parameters of type Example

Modifier and Type	Method and Description
Prediction<Regressor>	LinearSGDModel.predict(Example<Regressor> example)

Uses of Example in org.tribuo.regression.slm

Methods in org.tribuo.regression.slm with parameters of type Example

Modifier and Type	Method and Description
protected SparseVector	SparseLinearModel.createFeatures(Example<Regressor> example) Creates the feature vector.
Optional<Excuse<Regressor>>	SparseLinearModel.getExcuse(Example<Regressor> example)

Uses of Example in org.tribuo.regression.xgboost

Methods in org.tribuo.regression.xgboost with parameters of type Example

Modifier and Type	Method and Description
List<Prediction<Regressor>>	XGBoostRegressionConverter.convertBatchOutput(ImmutableOutputInfo<Regressor> info, List<float[][]> probabilities, int[] numValidFeatures, Example<Regressor>[] examples)
Prediction<Regressor>	XGBoostRegressionConverter.convertOutput(ImmutableOutputInfo<Regressor> info, List<float[]> probabilities, int numValidFeatures, Example<Regressor> example)

Uses of Example in org.tribuo.sequence

Methods in org.tribuo.sequence that return Example

Modifier and Type	Method and Description
Example<T>	SequenceExample.get(int i) Gets the example found at the specified index.

Methods in org.tribuo.sequence that return types with arguments of type Example

Modifier and Type	Method and Description
Iterator<Example<T>>	SequenceExample.iterator()

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

Modifier and Type	Method and Description
void	SequenceExample.addExample(Example<T> e) Adds an Example to this sequence.

Constructor parameters in org.tribuo.sequence with type arguments of type Example

Constructor and Description
SequenceExample(List<Example<T>> examples) Creates a sequence example from the list of examples.
SequenceExample(List<Example<T>> examples, float weight) Creates a sequence example from the list of examples, setting the weight.

Uses of Example in org.tribuo.transform

Methods in org.tribuo.transform that return Example

Modifier and Type	Method and Description
<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.

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

Modifier and Type	Method and Description
Optional<Excuse<T>>	TransformedModel.getExcuse(Example<T> example)
Prediction<T>	TransformedModel.predict(Example<T> example)
<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.