Package | Description |
---|---|
org.tribuo.anomaly.liblinear |
Provides an interface to LibLinear-java for anomaly detection problems.
|
org.tribuo.classification.liblinear |
Provides an interface to LibLinear-java for classification problems.
|
org.tribuo.common.liblinear |
Provides base classes for using liblinear from Tribuo.
|
org.tribuo.regression.liblinear |
Provides an interface to liblinear for regression problems.
|
Modifier and Type | Class and Description |
---|---|
class |
LibLinearAnomalyModel
A
Model which wraps a LibLinear-java anomaly detection model. |
Modifier and Type | Method and Description |
---|---|
protected LibLinearModel<Event> |
LibLinearAnomalyTrainer.createModel(ModelProvenance provenance,
ImmutableFeatureMap featureIDMap,
ImmutableOutputInfo<Event> outputIDInfo,
List<de.bwaldvogel.liblinear.Model> models) |
Modifier and Type | Class and Description |
---|---|
class |
LibLinearClassificationModel
A
Model which wraps a LibLinear-java classification model. |
Modifier and Type | Method and Description |
---|---|
protected LibLinearModel<Label> |
LibLinearClassificationTrainer.createModel(ModelProvenance provenance,
ImmutableFeatureMap featureIDMap,
ImmutableOutputInfo<Label> outputIDInfo,
List<de.bwaldvogel.liblinear.Model> models) |
Modifier and Type | Method and Description |
---|---|
protected abstract LibLinearModel<T> |
LibLinearTrainer.createModel(ModelProvenance provenance,
ImmutableFeatureMap featureIDMap,
ImmutableOutputInfo<T> outputIDInfo,
List<de.bwaldvogel.liblinear.Model> models)
Construct the appropriate subtype of LibLinearModel for the prediction task.
|
LibLinearModel<T> |
LibLinearTrainer.train(Dataset<T> examples) |
LibLinearModel<T> |
LibLinearTrainer.train(Dataset<T> examples,
Map<String,com.oracle.labs.mlrg.olcut.provenance.Provenance> runProvenance) |
Modifier and Type | Class and Description |
---|---|
class |
LibLinearRegressionModel
A
Model which wraps a LibLinear-java model. |
Modifier and Type | Method and Description |
---|---|
protected LibLinearModel<Regressor> |
LibLinearRegressionTrainer.createModel(ModelProvenance provenance,
ImmutableFeatureMap featureIDMap,
ImmutableOutputInfo<Regressor> outputIDInfo,
List<de.bwaldvogel.liblinear.Model> models) |
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