Uses of Interface
org.tribuo.evaluation.Evaluation

Packages that use Evaluation

Package	Description
org.tribuo	Provides the core interfaces and classes for using Tribuo.
org.tribuo.anomaly.evaluation	Evaluation classes for anomaly detection.
org.tribuo.classification.evaluation	Evaluation classes for multi-class classification.
org.tribuo.clustering.evaluation	Evaluation classes for clustering.
org.tribuo.evaluation	Evaluation base classes, along with code for train/test splits and cross validation.
org.tribuo.interop.modelcard	ModelCard feature to allow more transparent model reporting.
org.tribuo.multilabel.evaluation	Evaluation classes for multi-label classification using MultiLabel.
org.tribuo.regression.evaluation	Evaluation classes for single or multi-dimensional regression.

Uses of Evaluation in org.tribuo

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

Modifier and Type	Method	Description
Evaluator<T,? extends Evaluation<T>>	OutputFactory.getEvaluator()	Gets an Evaluator suitable for measuring performance of predictions for the Output subclass.

Uses of Evaluation in org.tribuo.anomaly.evaluation

Subinterfaces of Evaluation in org.tribuo.anomaly.evaluation

Modifier and Type	Interface	Description
interface	AnomalyEvaluation	An Evaluation for anomaly detection Events.

Uses of Evaluation in org.tribuo.classification.evaluation

Subinterfaces of Evaluation in org.tribuo.classification.evaluation

Modifier and Type	Interface	Description
interface	ClassifierEvaluation<T extends Classifiable<T>>	Defines methods that calculate classification performance, used for both multi-class and multi-label classification.
interface	LabelEvaluation	Adds multi-class classification specific metrics to ClassifierEvaluation.

Uses of Evaluation in org.tribuo.clustering.evaluation

Subinterfaces of Evaluation in org.tribuo.clustering.evaluation

Modifier and Type	Interface	Description
interface	ClusteringEvaluation	An Evaluation for clustering tasks.

Uses of Evaluation in org.tribuo.evaluation

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

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	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.
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.

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

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>, 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>, R extends Evaluation<T>> Map<MetricID<T>,DescriptiveStats>	EvaluationAggregator.summarizeCrossValidation(List<com.oracle.labs.mlrg.olcut.util.Pair<R,Model<T>>> evaluations)	Summarize all fields of a list of evaluations produced by CrossValidation.

Uses of Evaluation in org.tribuo.interop.modelcard

Constructors in org.tribuo.interop.modelcard with parameters of type Evaluation

Modifier	Constructor	Description
	ModelCard(Model<?> model, Evaluation<?> evaluation)	Creates an instance of ModelCard that does not include any extracted metrics and has its UsageDetails set to null.
	ModelCard(Model<?> model, Evaluation<?> evaluation, Map<String,Double> testingMetrics)	Creates an instance of ModelCard that has its UsageDetails set to null.
	ModelCard(Model<?> model, Evaluation<?> evaluation, Map<String,Double> testingMetrics, UsageDetails usage)	Creates an instance of ModelCard.
	ModelCard(Model<?> model, Evaluation<?> evaluation, UsageDetails usage)	Creates an instance of ModelCard that does not include any extracted metrics.
	TestingDetails(Evaluation<?> evaluation)	Creates an instance of TestingDetails.
	TestingDetails(Evaluation<?> evaluation, Map<String,Double> testingMetrics)	Creates an instance of TestingDetails.

Uses of Evaluation in org.tribuo.multilabel.evaluation

Subinterfaces of Evaluation in org.tribuo.multilabel.evaluation

Modifier and Type	Interface	Description
interface	MultiLabelEvaluation	A MultiLabel specific ClassifierEvaluation.

Classes in org.tribuo.multilabel.evaluation that implement Evaluation

Modifier and Type	Class	Description
final class	MultiLabelEvaluationImpl	The implementation of a MultiLabelEvaluation using the default metrics.

Uses of Evaluation in org.tribuo.regression.evaluation

Subinterfaces of Evaluation in org.tribuo.regression.evaluation

Modifier and Type	Interface	Description
interface	RegressionEvaluation	Defines methods that calculate regression performance.