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