Package | Description |
---|---|
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.metrics |
This package contains the infrastructure classes for building evaluation metrics.
|
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 |
---|---|
MetricTarget<Event> |
AnomalyMetric.getTarget() |
Constructor and Description |
---|
AnomalyMetric(MetricTarget<Event> target,
String name,
ToDoubleBiFunction<MetricTarget<Event>,org.tribuo.anomaly.evaluation.AnomalyMetric.Context> impl)
Creates an anomaly detection metric, with a specific name, using the supplied evaluation function.
|
Constructor and Description |
---|
AnomalyMetric(MetricTarget<Event> target,
String name,
ToDoubleBiFunction<MetricTarget<Event>,org.tribuo.anomaly.evaluation.AnomalyMetric.Context> impl)
Creates an anomaly detection metric, with a specific name, using the supplied evaluation function.
|
Modifier and Type | Method and Description |
---|---|
MetricTarget<Label> |
LabelMetric.getTarget() |
Modifier and Type | Method and Description |
---|---|
ToDoubleBiFunction<MetricTarget<Label>,LabelMetric.Context> |
LabelMetrics.getImpl()
Returns the implementing function for this metric.
|
Modifier and Type | Method and Description |
---|---|
static <T extends Classifiable<T>> |
ConfusionMetrics.accuracy(MetricTarget<T> target,
ConfusionMatrix<T> cm)
Calculates the accuracy given this confusion matrix.
|
static double |
LabelMetrics.AUCROC(MetricTarget<Label> tgt,
List<Prediction<Label>> predictions)
Area under the ROC curve.
|
static double |
LabelMetrics.averagedPrecision(MetricTarget<Label> tgt,
List<Prediction<Label>> predictions) |
static <T extends Classifiable<T>> |
ConfusionMetrics.f1(MetricTarget<T> tgt,
ConfusionMatrix<T> cm)
Computes the F_1 score.
|
static <T extends Classifiable<T>> |
ConfusionMetrics.fn(MetricTarget<T> tgt,
ConfusionMatrix<T> cm)
Returns the number of false negatives, possibly averaged depending on the metric target.
|
LabelMetric |
LabelMetrics.forTarget(MetricTarget<Label> tgt)
Gets the LabelMetric wrapped around the supplied MetricTarget.
|
static <T extends Classifiable<T>> |
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>> |
ConfusionMetrics.fscore(MetricTarget<T> tgt,
ConfusionMatrix<T> cm,
double beta)
Computes the Fscore.
|
static <T extends Classifiable<T>> |
ConfusionMetrics.precision(MetricTarget<T> tgt,
ConfusionMatrix<T> cm)
Calculates the precision for this metric target.
|
static <T extends Classifiable<T>> |
ConfusionMetrics.recall(MetricTarget<T> tgt,
ConfusionMatrix<T> cm)
Calculates the recall for this metric target.
|
static <T extends Classifiable<T>> |
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>> |
ConfusionMetrics.tp(MetricTarget<T> tgt,
ConfusionMatrix<T> cm)
Returns the number of true positives, possibly averaged depending on the metric target.
|
Constructor and Description |
---|
LabelMetric(MetricTarget<Label> tgt,
String name,
ToDoubleBiFunction<MetricTarget<Label>,LabelMetric.Context> impl)
Construct a new
LabelMetric for the supplied metric target,
using the supplied function. |
Constructor and Description |
---|
LabelMetric(MetricTarget<Label> tgt,
String name,
ToDoubleBiFunction<MetricTarget<Label>,LabelMetric.Context> impl)
Construct a new
LabelMetric for the supplied metric target,
using the supplied function. |
Modifier and Type | Method and Description |
---|---|
MetricTarget<ClusterID> |
ClusteringMetric.getTarget() |
Modifier and Type | Method and Description |
---|---|
BiFunction<MetricTarget<ClusterID>,org.tribuo.clustering.evaluation.ClusteringMetric.Context,Double> |
ClusteringMetrics.getImpl() |
Modifier and Type | Method and Description |
---|---|
ClusteringMetric |
ClusteringMetrics.forTarget(MetricTarget<ClusterID> tgt) |
Constructor and Description |
---|
ClusteringMetric(MetricTarget<ClusterID> target,
String name,
BiFunction<MetricTarget<ClusterID>,org.tribuo.clustering.evaluation.ClusteringMetric.Context,Double> impl) |
Constructor and Description |
---|
ClusteringMetric(MetricTarget<ClusterID> target,
String name,
BiFunction<MetricTarget<ClusterID>,org.tribuo.clustering.evaluation.ClusteringMetric.Context,Double> impl) |
Modifier and Type | Method and Description |
---|---|
MetricTarget<T> |
EvaluationMetric.getTarget()
The target for this metric instance.
|
static <U extends Output<U>> |
MetricTarget.macroAverageTarget()
Get the singleton
MetricTarget which contains the EvaluationMetric.Average.MACRO . |
static <U extends Output<U>> |
MetricTarget.microAverageTarget()
Get the singleton
MetricTarget which contains the EvaluationMetric.Average.MICRO . |
Constructor and Description |
---|
MetricID(MetricTarget<T> target,
String metricName) |
Modifier and Type | Method and Description |
---|---|
MetricTarget<MultiLabel> |
MultiLabelMetric.getTarget() |
Modifier and Type | Method and Description |
---|---|
BiFunction<MetricTarget<MultiLabel>,org.tribuo.multilabel.evaluation.MultiLabelMetric.Context,Double> |
MultiLabelMetrics.getImpl()
Get the implementation function for this metric.
|
Modifier and Type | Method and Description |
---|---|
MultiLabelMetric |
MultiLabelMetrics.forTarget(MetricTarget<MultiLabel> tgt)
Get the metric for the supplied target.
|
Constructor and Description |
---|
MultiLabelMetric(MetricTarget<MultiLabel> target,
String name,
BiFunction<MetricTarget<MultiLabel>,org.tribuo.multilabel.evaluation.MultiLabelMetric.Context,Double> impl) |
Constructor and Description |
---|
MultiLabelMetric(MetricTarget<MultiLabel> target,
String name,
BiFunction<MetricTarget<MultiLabel>,org.tribuo.multilabel.evaluation.MultiLabelMetric.Context,Double> impl) |
Modifier and Type | Method and Description |
---|---|
MetricTarget<Regressor> |
RegressionMetric.getTarget() |
Modifier and Type | Method and Description |
---|---|
static double |
RegressionMetrics.explainedVariance(MetricTarget<Regressor> target,
RegressionSufficientStatistics sufficientStats)
Calculates the explained variance based on the supplied statistics.
|
static double |
RegressionMetrics.mae(MetricTarget<Regressor> target,
RegressionSufficientStatistics sufficientStats)
Calculates the Mean Absolute Error based on the supplied statistics.
|
static double |
RegressionMetrics.r2(MetricTarget<Regressor> target,
RegressionSufficientStatistics sufficientStats)
Calculates R^2 based on the supplied statistics.
|
static double |
RegressionMetrics.rmse(MetricTarget<Regressor> target,
RegressionSufficientStatistics sufficientStats)
Calculates the RMSE based on the supplied statistics.
|
Constructor and Description |
---|
RegressionMetric(MetricTarget<Regressor> tgt,
String name,
ToDoubleBiFunction<MetricTarget<Regressor>,org.tribuo.regression.evaluation.RegressionMetric.Context> impl)
Construct a new
RegressionMetric for the supplied metric target,
using the supplied function. |
RegressionMetric(MetricTarget<Regressor> tgt,
String name,
ToDoubleBiFunction<MetricTarget<Regressor>,org.tribuo.regression.evaluation.RegressionMetric.Context> impl,
boolean useExampleWeights)
Construct a new
RegressionMetric for the supplied metric target,
using the supplied function. |
Constructor and Description |
---|
RegressionMetric(MetricTarget<Regressor> tgt,
String name,
ToDoubleBiFunction<MetricTarget<Regressor>,org.tribuo.regression.evaluation.RegressionMetric.Context> impl)
Construct a new
RegressionMetric for the supplied metric target,
using the supplied function. |
RegressionMetric(MetricTarget<Regressor> tgt,
String name,
ToDoubleBiFunction<MetricTarget<Regressor>,org.tribuo.regression.evaluation.RegressionMetric.Context> impl,
boolean useExampleWeights)
Construct a new
RegressionMetric for the supplied metric target,
using the supplied function. |
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