Albertbol

const Matrix = require('./matrix')

module.exports = class NeuralNetwork {
  constructor(
    inputNodes,
    hiddenNodes,
    outputNodes,
    learningRate,
    bias,
    trainingCycles,

Albertbol

  adjustWeights(input, weights, bias, gradients) {
    const inputT = Matrix.transpose(input)
    const weightsDelta = Matrix.multiply(gradients, inputT)
    weights = Matrix.map(weights, { m: weightsDelta, add: true })
    bias = Matrix.map(bias, { m: gradients, add: true })
  }

Albertbol

  derivativeReLU(y) {
    return y <= 0 ? 0 : 1
  }

Albertbol

  calculateGradientDescent(input, error) {
    let gradients = Matrix.map(input, { func: this.derivativeReLU })
    gradients = Matrix.map(gradients, { m: error, multiply: true })
    gradients = Matrix.map(gradients, {
      number: this.learningRate,
      multiply: true,
    })
    return gradients
  }

Albertbol

  train(trainData) {
    for (let c = 0; c < this.trainingCycles; c++) {
      const randomPicked = Math.floor(Math.random() * trainData.length)
      const { output, hidden, input } = this.feedforward(
        trainData[randomPicked].input
      )
      const answer = Matrix.fromArray(trainData[randomPicked].answer)
      const outputError = Matrix.map(answer, { m: output, subtract: true })
      const outputGradients = this.calculateGradientDescent(output, outputError)
      this.adjustWeights(

Albertbol

const trainingData = [
  // Black
  { input: [0, 0, 0], answer: [1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] },
  ...
]

Albertbol

const mainColors = [
  'Black',
  'Blue',
  'Brown',
  'Cyan',
  'Green',
  'Grey',
  'Orange',
  'Pink',
  'Purple',

Albertbol

const mainColors = [
  'Black',
  'Blue',
  'Brown',
  'Cyan',
  'Green',
  'Grey',
  'Orange',
  'Pink',
  'Purple',

Albertbol

 ReLU(x) {
    return x > 0 ? x : 0.0
  }

Albertbol

  calculateFF(input, weights, bias) {
    let output = Matrix.multiply(weights, input)
    output = Matrix.map(output, { m: bias, add: true })
    output = Matrix.map(output, { func: this.ReLU })
    return output
  }