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.multilabel.evaluation |
Evaluation classes for multi-label classification using
MultiLabel . |
org.tribuo.regression.evaluation |
Evaluation classes for single or multi-dimensional regression.
|
Modifier and Type | Method and Description |
---|---|
Evaluator<T,? extends Evaluation<T>> |
OutputFactory.getEvaluator()
Gets an
Evaluator suitable for measuring performance of predictions for the Output subclass. |
Modifier and Type | Interface and Description |
---|---|
interface |
AnomalyEvaluation
An
Evaluation for anomaly detection Event s. |
Modifier and Type | Interface and 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 . |
Modifier and Type | Interface and Description |
---|---|
interface |
ClusteringEvaluation
An
Evaluation for clustering tasks. |
Modifier and Type | Class and 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
Evaluation s of a given Dataset using the given Model . |
class |
OnlineEvaluator<T extends Output<T>,E extends Evaluation<T>>
An evaluator which aggregates predictions and produces
Evaluation s
covering all the Prediction s it has seen or created. |
Modifier and Type | Method and Description |
---|---|
static <T extends Output<T>,R extends Evaluation<T>> |
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>> |
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>> |
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>> |
EvaluationAggregator.summarize(List<R> evaluations)
Summarize all fields of a list of evaluations.
|
static <T extends Output<T>,R extends Evaluation<T>> |
EvaluationAggregator.summarize(List<R> evaluations,
ToDoubleFunction<R> fieldGetter)
Summarize a single field of an evaluation across several evaluations.
|
Modifier and Type | Interface and Description |
---|---|
interface |
MultiLabelEvaluation
A
MultiLabel specific ClassifierEvaluation . |
Modifier and Type | Class and Description |
---|---|
class |
MultiLabelEvaluationImpl
The implementation of a
MultiLabelEvaluation using the default metrics. |
Modifier and Type | Interface and Description |
---|---|
interface |
RegressionEvaluation
Defines methods that calculate regression performance.
|
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