Uses of Interface
jsat.regression.UpdateableRegressor

Packages that use UpdateableRegressor

Package	Description
jsat.classifiers.boosting
jsat.classifiers.linear
jsat.classifiers.linear.kernelized
jsat.regression

Uses of UpdateableRegressor in jsat.classifiers.boosting

Classes in jsat.classifiers.boosting that implement UpdateableRegressor

Modifier and Type	Class and Description
class	UpdatableStacking This provides an implementation of the Stacking ensemble method meant for Updatable models.

Constructors in jsat.classifiers.boosting with parameters of type UpdateableRegressor

Constructor and Description
UpdatableStacking(UpdateableRegressor aggregatingRegressor, List<UpdateableRegressor> baseRegressors) Creates a new Stacking regressor
UpdatableStacking(UpdateableRegressor aggregatingRegressor, UpdateableRegressor... baseRegressors) Creates a new Stacking regressor.
UpdatableStacking(UpdateableRegressor aggregatingRegressor, UpdateableRegressor... baseRegressors) Creates a new Stacking regressor.

Constructor parameters in jsat.classifiers.boosting with type arguments of type UpdateableRegressor

Constructor and Description
UpdatableStacking(UpdateableRegressor aggregatingRegressor, List<UpdateableRegressor> baseRegressors) Creates a new Stacking regressor

Uses of UpdateableRegressor in jsat.classifiers.linear

Classes in jsat.classifiers.linear that implement UpdateableRegressor

Modifier and Type	Class and Description
class	LinearSGD LinearSGD learns either a classification or regression problem depending on the loss function ℓ(w,x) used.
class	PassiveAggressive An implementations of the 3 versions of the Passive Aggressive algorithm for binary classification and regression.
class	STGD This provides an implementation of Sparse Truncated Gradient Descent for L1 regularized linear classification and regression on sparse data sets.

Uses of UpdateableRegressor in jsat.classifiers.linear.kernelized

Classes in jsat.classifiers.linear.kernelized that implement UpdateableRegressor

Modifier and Type	Class and Description
class	KernelSGD Kernel SGD is the kernelized counterpart to LinearSGD, and learns nonlinear functions via the kernel trick.

Uses of UpdateableRegressor in jsat.regression

Classes in jsat.regression that implement UpdateableRegressor

Modifier and Type	Class and Description
class	BaseUpdateableRegressor A base implementation of the UpdateableRegressor.
class	KernelRLS Provides an implementation of the Kernel Recursive Least Squares algorithm.

Methods in jsat.regression that return UpdateableRegressor

Modifier and Type	Method and Description
UpdateableRegressor	UpdateableRegressor.clone()
abstract UpdateableRegressor	BaseUpdateableRegressor.clone()

Methods in jsat.regression with parameters of type UpdateableRegressor

Modifier and Type	Method and Description
static void	BaseUpdateableRegressor.trainEpochs(RegressionDataSet dataSet, UpdateableRegressor toTrain, int epochs) Performs training on an updateable classifier by going over the whole data set in random order one observation at a time, multiple times.