Documentation
¶
Overview ¶
Package options defines training options for specific regression variants.
Index ¶
Constants ¶
This section is empty.
Variables ¶
This section is empty.
Functions ¶
This section is empty.
Types ¶
type ConverganceType ¶
type ConverganceType int
ConverganceType identifies a convergance type.
const ( Iterative ConverganceType = iota + 1 Automatic )
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 a iterative regression algorithm.
func WithAutomaticConvergance ¶
func WithAutomaticConvergance(lr float64, gdv GradientDescentVariant, t float64) Options
WithAutomaticConvergance returns new Options with an automatic convergance indicator.
func WithIterativeConvergance ¶
func WithIterativeConvergance(lr float64, gdv GradientDescentVariant, i uint) Options
WithIterativeConvergance returns new Options with an iterative convergance indicator.
func (Options) ConverganceIndicator ¶
ConverganceIndicator returns a convergance indicator.
func (Options) ConverganceType ¶
func (opt Options) ConverganceType() ConverganceType
ConverganceType returns a convergance 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
Click to show internal directories.
Click to hide internal directories.