mlregression

Documentation

Index

• func ComputeCost(data [][]float64, y []float64, theta []float64) (float64, error)
• func ComputeHypothesis(x []float64, theta []float64) float64
• func ComputeHypothesisVectorized(theta mat.Matrix, data mat.Matrix) mat.Matrix
• func LinearGradient(data [][]float64, y []float64, theta []float64, alpha float64, num_iters int, ...) ([]float64, error)
• func Normalize(input [][]float64) ([][]float64, []float64, []float64, error)
• type Data
• type Learner
  • func NewSliceLearner() Learner
• type Predictor
• type SliceLearner
  • func (l *SliceLearner) Learn(src Data, alpha float64, numIter int) (Predictor, error)
• type SlicePredictor
  • func (p *SlicePredictor) PredictOne(ins []float64) float64

Functions

func ComputeCost

func ComputeCost(data [][]float64, y []float64, theta []float64) (float64, error)

func ComputeHypothesis

func ComputeHypothesis(x []float64, theta []float64) float64

func ComputeHypothesisVectorized

func ComputeHypothesisVectorized(theta mat.Matrix, data mat.Matrix) mat.Matrix

func LinearGradient

func LinearGradient(data [][]float64, y []float64, theta []float64, alpha float64, num_iters int, printCostFunction bool) ([]float64, error)

func Normalize

func Normalize(input [][]float64) ([][]float64, []float64, []float64, error)

Types

type Data

type Data interface {
	Inputs() [][]float64
	Output() []float64
}

type Learner

type Learner interface {
	Learn(src Data, alpha float64, numIter int) (Predictor, error)
}

func NewSliceLearner

func NewSliceLearner() Learner

type Predictor

type Predictor interface {
	PredictOne(ins []float64) float64
}

type SliceLearner

type SliceLearner struct {
}

func (*SliceLearner) Learn

func (l *SliceLearner) Learn(src Data, alpha float64, numIter int) (Predictor, error)

type SlicePredictor

type SlicePredictor struct {
	NumInputs int
	Theta     []float64
	M         []float64
	S         []float64
}

func (*SlicePredictor) PredictOne

func (p *SlicePredictor) PredictOne(ins []float64) float64