Uses of Interface
org.tribuo.classification.Classifiable

Packages that use Classifiable

Package	Description
org.tribuo.classification	Provides classes and infrastructure for multiclass classification problems.
org.tribuo.classification.evaluation	Evaluation classes for multi-class classification.
org.tribuo.multilabel	Provides classes and infrastructure for working with multi-label classification problems.

Uses of Classifiable in org.tribuo.classification

Classes in org.tribuo.classification with type parameters of type Classifiable

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 Classifiable

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

Uses of Classifiable in org.tribuo.classification.evaluation

Classes in org.tribuo.classification.evaluation with type parameters of type Classifiable

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	ConfusionMatrix<T extends Classifiable<T>>	A confusion matrix for Classifiables.

Methods in org.tribuo.classification.evaluation with type parameters of type Classifiable

Modifier and Type	Method	Description
static <T extends Classifiable<T>> double	ConfusionMetrics.accuracy(EvaluationMetric.Average average, ConfusionMatrix<T> cm)	Calculates the accuracy using the specified average type and confusion matrix.
static <T extends Classifiable<T>> double	ConfusionMetrics.accuracy(MetricTarget<T> target, ConfusionMatrix<T> cm)	Calculates the accuracy given this confusion matrix.
static <T extends Classifiable<T>> double	ConfusionMetrics.accuracy(T label, ConfusionMatrix<T> cm)	Calculates a per label accuracy given this confusion matrix.
static <T extends Classifiable<T>> double	ConfusionMetrics.balancedErrorRate(ConfusionMatrix<T> cm)	Calculates the balanced error rate, i.e., the mean of the recalls.
static <T extends Classifiable<T>> double	ConfusionMetrics.f1(MetricTarget<T> tgt, ConfusionMatrix<T> cm)	Computes the F_1 score.
static <T extends Classifiable<T>> double	ConfusionMetrics.fn(MetricTarget<T> tgt, ConfusionMatrix<T> cm)	Returns the number of false negatives, possibly averaged depending on the metric target.
static <T extends Classifiable<T>> double	ConfusionMetrics.fp(MetricTarget<T> tgt, ConfusionMatrix<T> cm)	Returns the number of false positives, possibly averaged depending on the metric target.
static <T extends Classifiable<T>> double	ConfusionMetrics.fscore(MetricTarget<T> tgt, ConfusionMatrix<T> cm, double beta)	Computes the Fscore.
static <T extends Classifiable<T>> double	ConfusionMetrics.precision(MetricTarget<T> tgt, ConfusionMatrix<T> cm)	Calculates the precision for this metric target.
static <T extends Classifiable<T>> double	ConfusionMetrics.recall(MetricTarget<T> tgt, ConfusionMatrix<T> cm)	Calculates the recall for this metric target.
static <T extends Classifiable<T>> double	ConfusionMatrix.sumOverOutputs(ImmutableOutputInfo<T> domain, ToDoubleFunction<T> getter)	Sums the supplied getter over the domain.
static <T extends Classifiable<T>> double	ConfusionMetrics.tn(MetricTarget<T> tgt, ConfusionMatrix<T> cm)	Returns the number of true negatives, possibly averaged depending on the metric target.
static <T extends Classifiable<T>> double	ConfusionMetrics.tp(MetricTarget<T> tgt, ConfusionMatrix<T> cm)	Returns the number of true positives, possibly averaged depending on the metric target.

Uses of Classifiable in org.tribuo.multilabel

Classes in org.tribuo.multilabel that implement Classifiable

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