Uses of Interface
org.tribuo.math.Parameters
Packages that use Parameters
Package
Description
Provides an implementation of a linear chain CRF trained using Stochastic Gradient Descent.
Provides the base classes for models trained with stochastic gradient descent.
Contains the implementation of Tribuo's math library, it's gradient descent optimisers, kernels and a set of
math related utils.
Provides implementations of
StochasticGradientOptimiser
.-
Uses of Parameters in org.tribuo.classification.sgd.crf
Classes in org.tribuo.classification.sgd.crf that implement Parameters -
Uses of Parameters in org.tribuo.common.sgd
Classes in org.tribuo.common.sgd that implement Parameters -
Uses of Parameters in org.tribuo.math
Subinterfaces of Parameters in org.tribuo.mathModifier and TypeInterfaceDescriptioninterface
A Parameters for models which make a single prediction like logistic regressions and neural networks.Classes in org.tribuo.math that implement ParametersMethods in org.tribuo.math with parameters of type ParametersModifier and TypeMethodDescriptiondefault void
StochasticGradientOptimiser.initialise
(Parameters parameters) Initialises the gradient optimiser. -
Uses of Parameters in org.tribuo.math.optimisers
Methods in org.tribuo.math.optimisers with parameters of type ParametersModifier and TypeMethodDescriptionvoid
AdaDelta.initialise
(Parameters parameters) void
AdaGrad.initialise
(Parameters parameters) void
AdaGradRDA.initialise
(Parameters parameters) void
Adam.initialise
(Parameters parameters) void
ParameterAveraging.initialise
(Parameters parameters) void
Pegasos.initialise
(Parameters parameters) void
RMSProp.initialise
(Parameters parameters) void
SGD.initialise
(Parameters parameters)