nn

Documentation

Index

• func Sigmoid(x float64) float64
• func SigmoidDerivative(x float64) float64
• type Layer
  • func (l *Layer) Forward(inputs []float64) []float64
• type NeuralNetwork
  • func NewNeuralNetwork(structure []int) *NeuralNetwork
  • func (nn *NeuralNetwork) BackPropagate(inputs []float64, expected []float64, learnRate float64)
  • func (nn *NeuralNetwork) Forward(inputs []float64) []float64
• type Neuron
  • func (n *Neuron) Forward(inputs []float64) float64

Functions

func Sigmoid

func Sigmoid(x float64) float64

Sigmoid 激活函数及其导数

func SigmoidDerivative

func SigmoidDerivative(x float64) float64

Types

type Layer

type Layer struct {
	// contains filtered or unexported fields
}

Layer structure

func (*Layer) Forward

func (l *Layer) Forward(inputs []float64) []float64

Forward pass for a layer

type NeuralNetwork

type NeuralNetwork struct {
	// contains filtered or unexported fields
}

NeuralNetwork structure

func NewNeuralNetwork

func NewNeuralNetwork(structure []int) *NeuralNetwork

Initialize the network with the number of neurons in each layer

func (*NeuralNetwork) BackPropagate

func (nn *NeuralNetwork) BackPropagate(inputs []float64, expected []float64, learnRate float64)

Backpropagation and weight update

func (*NeuralNetwork) Forward

func (nn *NeuralNetwork) Forward(inputs []float64) []float64

Forward pass for the network

type Neuron

type Neuron struct {
	Weights []float64
	Bias    float64
}

Neuron structure

func (*Neuron) Forward

func (n *Neuron) Forward(inputs []float64) float64

Forward pass for a neuron