Package | Description |
---|---|
org.tribuo |
Provides the core interfaces and classes for using Tribuo.
|
org.tribuo.classification.explanations.lime |
Provides an implementation of LIME (Locally Interpretable Model Explanations).
|
org.tribuo.common.tree |
Provides common functionality for building decision trees, irrespective
of the predicted
Output . |
org.tribuo.regression.impl | |
org.tribuo.regression.rtree |
Provides an implementation of decision trees for regression problems.
|
org.tribuo.regression.slm |
Provides implementations of sparse linear regression using various forms of regularisation penalty.
|
Modifier and Type | Method and Description |
---|---|
SparseModel<T> |
SparseModel.copy() |
default SparseModel<T> |
SparseTrainer.train(Dataset<T> examples)
Trains a sparse predictive model using the examples in the given data set.
|
SparseModel<T> |
SparseTrainer.train(Dataset<T> examples,
Map<String,com.oracle.labs.mlrg.olcut.provenance.Provenance> runProvenance)
Trains a sparse predictive model using the examples in the given data set.
|
Modifier and Type | Method and Description |
---|---|
SparseModel<Regressor> |
LIMEExplanation.getModel() |
protected SparseModel<Regressor> |
LIMEBase.trainExplainer(Example<Regressor> target,
List<Example<Regressor>> samples)
Trains the explanation model using the supplied sampled data and the input example.
|
Constructor and Description |
---|
LIMEExplanation(SparseModel<Regressor> model,
Prediction<Label> prediction,
RegressionEvaluation evaluation) |
Modifier and Type | Class and Description |
---|---|
class |
TreeModel<T extends Output<T>>
|
Modifier and Type | Class and Description |
---|---|
class |
SkeletalIndependentRegressionSparseModel
A
SparseModel which wraps n independent regression models, where n is the
size of the MultipleRegressor domain. |
Modifier and Type | Class and Description |
---|---|
class |
IndependentRegressionTreeModel
|
Modifier and Type | Class and Description |
---|---|
class |
SparseLinearModel
The inference time version of a sparse linear regression model.
|
Modifier and Type | Method and Description |
---|---|
SparseModel<Regressor> |
ElasticNetCDTrainer.train(Dataset<Regressor> examples,
Map<String,com.oracle.labs.mlrg.olcut.provenance.Provenance> runProvenance) |
Copyright © 2015–2021 Oracle and/or its affiliates. All rights reserved.