mlearning

Documentation

Overview

Package mlearning provides a few abstracted machine learning algorithms.

Index

• type Class
• type Feature
• type FeatureCollection
• type Iterator
• type Model
  • func NewModel() *Model
• type Perceptron
  • func NewPerceptron() *Perceptron
  • func (p *Perceptron) Predict(features []Feature) (Class, Weight)
  • func (p *Perceptron) PredictAll(features []Feature) []Prediction
  • func (p *Perceptron) Test(fs Iterator) (int, int)
  • func (p *Perceptron) Train(fs Iterator) (int, int)
  • func (p *Perceptron) Update(truth Class, guess Class, features []Feature)
  • func (p *Perceptron) UpdateFeature(c Class, f Feature, w Weight)
• type Prediction
• type SimpleIterator
  • func (i *SimpleIterator) Class() Class
  • func (i *SimpleIterator) Features() []Feature
  • func (i *SimpleIterator) Next() bool
  • func (i *SimpleIterator) Predicted(c Class)
  • func (i *SimpleIterator) Reset(shuffle bool)
• type Weight

Types

type Class

type Class string

type Feature

type Feature string

type FeatureCollection

type FeatureCollection interface {
	Features() []Feature
}

type Iterator

type Iterator interface {
	Next() bool
	Features() []Feature
	Class() Class
	Predicted(c Class)
}

type Model

type Model struct {
	Weights map[Feature]map[Class]Weight
	Classes []Class

	I          int
	Totals     map[Feature]map[Class]Weight
	Timestamps map[Feature]map[Class]int
}

func NewModel

func NewModel() *Model

type Perceptron

type Perceptron struct {
	*Model
}

func NewPerceptron

func NewPerceptron() *Perceptron

func (*Perceptron) Predict

func (p *Perceptron) Predict(features []Feature) (Class, Weight)

func (*Perceptron) PredictAll

func (p *Perceptron) PredictAll(features []Feature) []Prediction

func (*Perceptron) Test

func (p *Perceptron) Test(fs Iterator) (int, int)

func (*Perceptron) Train

func (p *Perceptron) Train(fs Iterator) (int, int)

func (*Perceptron) Update

func (p *Perceptron) Update(truth Class, guess Class, features []Feature)

func (*Perceptron) UpdateFeature

func (p *Perceptron) UpdateFeature(c Class, f Feature, w Weight)

type Prediction

type Prediction struct {
	Class  Class
	Weight Weight
}

type SimpleIterator

type SimpleIterator struct {
	Index          int
	FeatureSlice   []FeatureCollection
	ClassSlice     []Class
	PredictedSlice []Class
}

func (*SimpleIterator) Class

func (i *SimpleIterator) Class() Class

func (*SimpleIterator) Features

func (i *SimpleIterator) Features() []Feature

func (*SimpleIterator) Next

func (i *SimpleIterator) Next() bool

func (*SimpleIterator) Predicted

func (i *SimpleIterator) Predicted(c Class)

func (*SimpleIterator) Reset

func (i *SimpleIterator) Reset(shuffle bool)

type Weight

type Weight float64