[英]Neural Network in JavaScript
我的神經網絡有點麻煩。 我已經設置好了,它會生成一個包含5個值的數組; 0
或1
,即[1,1,0,1,0]
。 然后使用Node.js控制台記錄隨機數組,如果我回答y
,它將以正確的輸出將其添加到訓練中,反之亦然。 有一次,我已經回應的genRan()
運行,並創建一個新的隨機排列,並保存了“猜”對var guess
。 但是,在第一次運行后,它不再給我一個猜測值,而是: [object Object]
。
這是代碼:
var brain = require('brain.js');
var net = new brain.NeuralNetwork();
const readline = require('readline');
const r1 = readline.createInterface({
input: process.stdin,
output: process.stdout
});
var ca = 0,
wa = 0;
net.train([
{input: [0,0,0,0,0], output: [0]}
]);
function genRan(){
var a,b,c,d,e;
var array = [];
a = Math.round(Math.random());
b = Math.round(Math.random());
c = Math.round(Math.random());
d = Math.round(Math.random());
e = Math.round(Math.random());
array.push(a,b,c,d,e);
var guess = net.run(array);
ask(array,guess);
}
function ask(a,b){
var array = a,
guess = b;
r1.question((wa+ca) + ") input: " + array + " We think: " + guess + ". Am I correct? (Y/N)", (answer) => {
if(answer == "Y" || answer == "y"){
ca++;
net.train([
{input : array, output : Math.round(guess)}
]);
}else if(answer == "N" || answer == "n"){
wa++;
var roundGuess = Math.round(guess);
var opposite;
switch (roundGuess){
case 1:
opposite = 0;
break;
case 0:
opposite = 1;
break;
default:
opposite = null
}
net.train([
{input : array, output : opposite}
]);
}
console.log("Success percent: " + (100 *ca/(ca+wa)) + "% " + (ca+wa) +" attempts\n\r");
genRan();
})
}
genRan();
第一個問題工作正常,並提出以下內容:
0) input: 0,0,0,0,0 We think: 0.07046. Am I correct? (Y/N)
當我回復時,我得到:
Success percent: 100% 1 attempts
1) input 1,1,1,0,1 We think: [object Object]. Am I correct? (Y/N)
出於某種原因,當談到“猜測”時,它並沒有給我任何價值。 有什么想法嗎?
它出錯的原因是雙重的
net.run
的輸出是一個數組-您可能需要其中的第一項。 net.train
output
的輸入是一個數組-您正在為其傳遞一個不同的值 經過一些更改,您的代碼將按您期望的那樣工作:
ask
方法中始終使用guess[0]
將oposite
變量包裝在方括號中以使其成為數組
net.train([ {input : array, output : [opposite]} ]);
以下工作代碼供您參考(盡管不會在stacksnippet中工作)
var brain = require('brain.js'); var net = new brain.NeuralNetwork(); const readline = require('readline'); const r1 = readline.createInterface({ input: process.stdin, output: process.stdout }); var ca = 0, wa = 0; net.train([ {input: [0,0,0,0,0], output: [0]} ]); function genRan(){ var a,b,c,d,e; var array = []; a = Math.round(Math.random()); b = Math.round(Math.random()); c = Math.round(Math.random()); d = Math.round(Math.random()); e = Math.round(Math.random()); array.push(a,b,c,d,e); //console.log(array); var guess = net.run(array); ask(array,guess); } function ask(a,b){ var array = a, guess = b; r1.question((wa+ca) + ") input: " + array + " We think: " + guess[0] + ". Am I correct? (Y/N)", (answer) => { if(answer == "Y" || answer == "y"){ ca++; net.train([ {input : array, output : Math.round(guess[0])} ]); }else if(answer == "N" || answer == "n"){ wa++; var roundGuess = Math.round(guess[0]); var opposite; switch (roundGuess){ case 1: opposite = 0; break; case 0: opposite = 1; break; default: opposite = null } net.train([ {input : array, output : [opposite]} ]); } console.log("Success percent: " + (100 *ca/(ca+wa)) + "% " + (ca+wa) +" attempts\\n\\r"); genRan(); }) } genRan();
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