Package | Description |
---|---|
org.tribuo.classification.sgd.linear |
Provides an implementation of a classification linear model using Stochastic Gradient Descent.
|
org.tribuo.common.sgd |
Provides the base classes for models trained with stochastic gradient descent.
|
org.tribuo.math |
Contains the implementation of Tribuo's math library, it's gradient descent optimisers, kernels and a set of
math related utils.
|
org.tribuo.multilabel.sgd.linear |
Provides an implementation of a multi-label classification linear model using Stochastic Gradient Descent.
|
org.tribuo.regression.sgd.linear |
Provides an implementation of linear regression using Stochastic Gradient Descent.
|
Modifier and Type | Method and Description |
---|---|
protected LinearSGDModel |
LinearSGDTrainer.createModel(String name,
ModelProvenance provenance,
ImmutableFeatureMap featureMap,
ImmutableOutputInfo<Label> outputInfo,
LinearParameters parameters) |
Modifier and Type | Method and Description |
---|---|
protected LinearParameters |
AbstractLinearSGDTrainer.createParameters(int numFeatures,
int numOutputs,
SplittableRandom localRNG)
Constructs the trainable parameters object, in this case a
LinearParameters containing
a single weight matrix. |
Constructor and Description |
---|
AbstractLinearSGDModel(String name,
ModelProvenance provenance,
ImmutableFeatureMap featureIDMap,
ImmutableOutputInfo<T> outputIDInfo,
LinearParameters parameters,
boolean generatesProbabilities)
Constructs a linear model trained via SGD.
|
Modifier and Type | Method and Description |
---|---|
LinearParameters |
LinearParameters.copy() |
Modifier and Type | Method and Description |
---|---|
protected LinearSGDModel |
LinearSGDTrainer.createModel(String name,
ModelProvenance provenance,
ImmutableFeatureMap featureMap,
ImmutableOutputInfo<MultiLabel> outputInfo,
LinearParameters parameters) |
Modifier and Type | Method and Description |
---|---|
protected LinearSGDModel |
LinearSGDTrainer.createModel(String name,
ModelProvenance provenance,
ImmutableFeatureMap featureMap,
ImmutableOutputInfo<Regressor> outputInfo,
LinearParameters parameters) |
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