Another simple 'perceptron' implementing a bias to work with both AND / OR

OR_AND_perceptron.js

var inputs = [
  [0,0],
  [1,0],
  [0,1],
  [1,1]
]

var outputs = [
  // AND
  // 0, 0, 0, 1
  // OR
  0, 1, 1, 1
]

var weights = [
  0, 1
]

var limit = 1000
var count = 0

function train(){

  for(var i in inputs){

    var bias = 0.5
    var sum = 0
    for(var w in weights){
      sum += weights[w] * (inputs[i][w] + bias)
    }

    var output = sum > 1 ? 1 : 0;

    console.log('---------------------------')
    console.log(count + ',' + i)
    console.log('outputs ' + output + ':' + outputs[i])
    console.log('weights ' + weights)
    console.log('sum ' + sum)

    if(output == outputs[i]){
      console.log('correct')
    }
    else{
      console.log('---------------------------')
      console.log('incorrect')
      for(var w in weights){
        weights[w] = (Math.floor(Math.random() * 10) + 0) / 10
        console.log(weights[w])
      }
      if(count < limit){
        count++
        train()
      }
    }

  }

}

train();