Uses of Interface
org.tribuo.math.StochasticGradientOptimiser

Packages that use StochasticGradientOptimiser

Package	Description
org.tribuo.classification.sgd.crf	Provides an implementation of a linear chain CRF trained using Stochastic Gradient Descent.
org.tribuo.classification.sgd.linear	Provides an implementation of a classification linear model using 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.math.optimisers	Provides implementations of StochasticGradientOptimiser.
org.tribuo.regression.sgd.linear	Provides an implementation of linear regression using Stochastic Gradient Descent.

Uses of StochasticGradientOptimiser in org.tribuo.classification.sgd.crf

Constructors in org.tribuo.classification.sgd.crf with parameters of type StochasticGradientOptimiser

Modifier	Constructor	Description
	CRFTrainer(StochasticGradientOptimiser optimiser, int epochs, int loggingInterval, int minibatchSize, long seed)	Creates a CRFTrainer which uses SGD to learn the parameters.
	CRFTrainer(StochasticGradientOptimiser optimiser, int epochs, int loggingInterval, long seed)	Sets the minibatch size to 1.
	CRFTrainer(StochasticGradientOptimiser optimiser, int epochs, long seed)	Sets the minibatch size to 1 and the logging interval to 100.

Uses of StochasticGradientOptimiser in org.tribuo.classification.sgd.linear

Constructors in org.tribuo.classification.sgd.linear with parameters of type StochasticGradientOptimiser

Modifier	Constructor	Description
	LinearSGDTrainer(LabelObjective objective, StochasticGradientOptimiser optimiser, int epochs, int loggingInterval, int minibatchSize, long seed)	Constructs an SGD trainer for a linear model.
	LinearSGDTrainer(LabelObjective objective, StochasticGradientOptimiser optimiser, int epochs, int loggingInterval, long seed)	Sets the minibatch size to 1.
	LinearSGDTrainer(LabelObjective objective, StochasticGradientOptimiser optimiser, int epochs, long seed)	Sets the minibatch size to 1 and the logging interval to 1000.

Uses of StochasticGradientOptimiser in org.tribuo.math

Methods in org.tribuo.math that return StochasticGradientOptimiser

Modifier and Type	Method	Description
StochasticGradientOptimiser	StochasticGradientOptimiser.copy()	Copies a gradient optimiser with it's configuration.

Uses of StochasticGradientOptimiser in org.tribuo.math.optimisers

Classes in org.tribuo.math.optimisers that implement StochasticGradientOptimiser

Modifier and Type	Class	Description
class	AdaDelta	An implementation of the AdaDelta gradient optimiser.
class	AdaGrad	An implementation of the AdaGrad gradient optimiser.
class	AdaGradRDA	An implementation of the AdaGrad gradient optimiser with regularized dual averaging.
class	Adam	An implementation of the Adam gradient optimiser.
class	ParameterAveraging	Averages the parameters across a gradient run.
class	Pegasos	An implementation of the Pegasos gradient optimiser used primarily for solving the SVM problem.
class	RMSProp	An implementation of the RMSProp gradient optimiser.
class	SGD	An implementation of single learning rate SGD and optionally momentum.

Methods in org.tribuo.math.optimisers that return StochasticGradientOptimiser

Modifier and Type	Method	Description
StochasticGradientOptimiser	GradientOptimiserOptions.getOptimiser()	Gets the configured gradient optimiser.

Constructors in org.tribuo.math.optimisers with parameters of type StochasticGradientOptimiser

Modifier	Constructor	Description
	ParameterAveraging(StochasticGradientOptimiser optimiser)	Adds parameter averaging around a gradient optimiser.

Uses of StochasticGradientOptimiser in org.tribuo.regression.sgd.linear

Constructors in org.tribuo.regression.sgd.linear with parameters of type StochasticGradientOptimiser

Modifier	Constructor	Description
	LinearSGDTrainer(RegressionObjective objective, StochasticGradientOptimiser optimiser, int epochs, int loggingInterval, int minibatchSize, long seed)	Constructs an SGD trainer for a linear model.
	LinearSGDTrainer(RegressionObjective objective, StochasticGradientOptimiser optimiser, int epochs, int loggingInterval, long seed)	Sets the minibatch size to 1.
	LinearSGDTrainer(RegressionObjective objective, StochasticGradientOptimiser optimiser, int epochs, long seed)	Sets the minibatch size to 1 and the logging interval to 1000.