Uses of Class
org.ddogleg.optimization.loss.LossFunctionBase

Packages that use LossFunctionBase

Package	Description
org.ddogleg.optimization.loss

Uses of LossFunctionBase in org.ddogleg.optimization.loss

Subclasses of LossFunctionBase in org.ddogleg.optimization.loss

Modifier and Type	Class	Description
class	LossCauchy	Loss function inspired by the Cauchy distribution, a.k.a Lorentzian loss function.
static class	LossCauchy.Function	Implementation of the smooth Cauchy loss function
static class	LossCauchy.Gradient	Implementation of the smooth Cauchy loss gradient
class	LossHuber	Huber Loss is a robust loss function that is less sensitive to outliers than the squared error loss.
static class	LossHuber.Function	Implementation of the Huber loss function
static class	LossHuber.Gradient	Implementation of the Huber Loss gradient
class	LossHuberSmooth	Smooth approximation to the huber loss [1].
static class	LossHuberSmooth.Function	Implementation of the smooth Huber loss function
static class	LossHuberSmooth.Gradient	Implementation of the smooth Huber loss gradient
class	LossIdentity	This loss function simply passes through the computed "residual".
static class	LossIdentity.Function
static class	LossIdentity.Gradient
class	LossSquared	Squared error loss function.
static class	LossSquared.Function
static class	LossSquared.Gradient
class	LossTukey	Tukey loss (Tukey's biweight function) has similar behavior to LossHuber but is less sensitive to outliers because they contribute nothing to the loss.
static class	LossTukey.Function	Implementation of the Tukey loss function
static class	LossTukey.Gradient	Implementation of the Tukey Loss gradient