@ralphschuler.neuronal network.Network

Class: Network<T>

@ralphschuler/neuronal-network.Network

Type parameters

Name
T

Table of contents

Constructors

• constructor

Properties

• hiddenLayers
• inputLayer
• outputLayer

Methods

• activate
• connect
• propagate
• toObject
• train

Constructors

constructor

• new Network<T>(inputLayerLength, hiddenLayerLengths, outputLayerLength, createNeuron): Network<T>

Type parameters

Name
T

Parameters

Name	Type
inputLayerLength	number
hiddenLayerLengths	number[]
outputLayerLength	number
createNeuron	(bias: number) => Neuron<T>

Returns

Network<T>

Defined in

index.ts:78

Properties

hiddenLayers

• Private hiddenLayers: Layer<T>[] = []

Defined in

index.ts:75

---

inputLayer

• Private inputLayer: Layer<T>

Defined in

index.ts:74

---

outputLayer

• Private outputLayer: Layer<T>

Defined in

index.ts:76

Methods

activate

▸ activate(input): T[]

Parameters

Name	Type
input	T[]

Returns

T[]

Defined in

index.ts:99

---

connect

▸ connect(): void

Returns

void

Defined in

index.ts:91

---

propagate

▸ propagate(error): void

Parameters

Name	Type
error	T[]

Returns

void

Defined in

index.ts:108

---

toObject

▸ toObject(): object

Returns

object

Defined in

index.ts:125

---

train

▸ train(input, output): void

Parameters

Name	Type
input	T[]
output	T[]

Returns

void

Defined in

index.ts:117