Uses of Interface
org.tribuo.regression.sgd.RegressionObjective
Packages that use RegressionObjective
Package
Description
Provides an implementation of linear regression using Stochastic Gradient Descent.
Provides regression loss functions for Stochastic Gradient Descent.
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Uses of RegressionObjective in org.tribuo.regression.sgd.linear
Constructors in org.tribuo.regression.sgd.linear with parameters of type RegressionObjectiveModifierConstructorDescriptionLinearSGDTrainer
(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 RegressionObjectiveModifier and TypeClassDescriptionclass
Absolute loss (i.e., l1).class
Huber loss, i.e., a mixture of l2 and l1 losses.class
Squared loss, i.e., l2.