Uses of Interface
org.tribuo.regression.sgd.RegressionObjective

Packages that use RegressionObjective

Package	Description
org.tribuo.regression.sgd.linear	Provides an implementation of linear regression using Stochastic Gradient Descent.
org.tribuo.regression.sgd.objectives	Provides regression loss functions for Stochastic Gradient Descent.

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

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

Constructor and 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.

Uses of RegressionObjective in org.tribuo.regression.sgd.objectives

Classes in org.tribuo.regression.sgd.objectives that implement RegressionObjective

Modifier and Type	Class and Description
class	AbsoluteLoss Absolute loss (i.e., l1).
class	Huber Huber loss, i.e., a mixture of l2 and l1 losses.
class	SquaredLoss Squared loss, i.e., l2.