const nn = require("@jeff-tian/perceptron/lib/NeuralNetwork")
const flat = (prev, next)=>[...prev, ...next]
const getFlattedWeights = weights => weights.reduce(flat).reduce(flat)
const getNthWeights = index => '(' + getFlattedWeights(network.weightsHistory[index].weights).join(', ') + ')'
const network = nn.backPropFor2LevelSigmoidUnitForwardNetwork([
{
x: [1, 0],
t: 1,
},
{
x: [0, 1],
t: 0,
},
], 0.3, 0.9)
console.log("初始权值 = " + getNthWeights(0))
console.log("第一次迭代后的权值 = " + getNthWeights(1))
console.log("第二次迭代后的权值 = " + getNthWeights(2))
Created from: https://npm.runkit.com/%40jeff-tian%2Fperceptron
This is the solution for "Machine Learning"'s exercise 4.7: https://ml.jiwai.win/%E7%AC%AC%E5%9B%9B%E7%AB%A0%20%E4%BA%BA%E5%B7%A5%E7%A5%9E%E7%BB%8F%E7%BD%91%E7%BB%9C/4.7.html
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