Documentation
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Overview ¶
Package options contains implementation of types and constants related to the regression options.
Index ¶
Constants ¶
This section is empty.
Variables ¶
This section is empty.
Functions ¶
This section is empty.
Types ¶
type ConvergenceType ¶ added in v0.2.0
type ConvergenceType int
ConvergenceType identifies a convergence type.
const ( Iterative ConvergenceType = iota + 1 Automatic )
type FeatureScalingTechnique ¶ added in v0.2.0
type FeatureScalingTechnique int
FeatureScalingTechnique identifies a feature scaling technique.
const ( None FeatureScalingTechnique = iota Normalization Standarization )
type GradientDescentVariant ¶
type GradientDescentVariant int
GradientDescentVariant identifies a gradient descent variant.
const ( Batch GradientDescentVariant = iota + 1 Stochastic )
type Options ¶
type Options struct {
// contains filtered or unexported fields
}
Options contains training options for an iterative regression algorithm.
func WithAutomaticConvergence ¶ added in v0.2.0
func WithAutomaticConvergence(lr float64, gdv GradientDescentVariant, t float64) Options
WithAutomaticConvergence returns new Options with an automatic convergence indicator.
func WithIterativeConvergence ¶ added in v0.2.0
func WithIterativeConvergence(lr float64, gdv GradientDescentVariant, i uint) Options
WithIterativeConvergence returns new Options with an iterative convergence indicator.
func (Options) ConvergenceIndicator ¶ added in v0.2.0
ConvergenceIndicator returns a convergence indicator.
func (Options) ConvergenceType ¶ added in v0.2.0
func (opt Options) ConvergenceType() ConvergenceType
ConvergenceType returns a convergence type.
func (Options) GradientDescentVariant ¶
func (opt Options) GradientDescentVariant() GradientDescentVariant
GradientDescentVariant returns a gradient descent variant.
func (Options) LearningRate ¶
LearningRate returns a learning rate.
Source Files