Javascript NOT函数的布尔感知器
我试图为基本布尔表达式实现一个简单的感知器。但是我不能正确地训练非感知器 我成功地训练了和以及或感知器返回给定输入集的正确值。但是当我试图训练时，却不是 我就是这样做的： 和以及或感知机有两个输入，两个权重和一个偏差（偏差输入固定为1） 所有感知器在所有权重上均以0开始。 然后我生成随机值（介于0和1之间）来训练感知机，并保持循环，直到我得到10个正确的猜测 他们的学习率为0.1 这是培训过程： 要猜测值：Javascript NOT函数的布尔感知器,javascript,machine-learning,neural-network,boolean-logic,perceptron,Javascript,Machine Learning,Neural Network,Boolean Logic,Perceptron,我试图为基本布尔表达式实现一个简单的感知器。但是我不能正确地训练非感知器 我成功地训练了和以及或感知器返回给定输入集的正确值。但是当我试图训练时，却不是 我就是这样做的： 和以及或感知机有两个输入，两个权重和一个偏差（偏差输入固定为1） 所有感知器在所有权重上均以0开始。 然后我生成随机值（介于0和1之间）来训练感知机，并保持循环，直到我得到10个正确的猜测 他们的学习率为0.1 这是培训过程： 要猜测值： 对于每个输入，我将输入乘以权重，并将所有值相加，包括偏差 sum = (weight1
对于每个输入，我将输入乘以权重，并将所有值相加，包括偏差
sum = (weight1 * input1) + (weight2 * input2) + (biasWeight * biasInput)--Bias input is fixed to 1
return = if (sum > 0) then 1 else 0
我从感知机那里得到了猜测
val = and.guess(1,0) --This will return 0 or 1
error = answer - val
weight = weight + (input * error * rate)
biasWeight = biasWeight + (input * error * rate)--Bias input is fixed to 1
<!DOCTYPE html>
<html lang="en" xmlns="http://www.w3.org/1999/xhtml">
<head>
<meta charset="utf-8" />
<title></title>
<script src="jquery-3.2.1.js"></script>
<script type="text/javascript">
function Show(text) {
if (!text) {
text = '';
}
document.writeln(text + '<br />');
}
//return random value from 0 ~ 1
function getRandom() {
return Math.floor(Math.random() * 2);
};
function PerceptronData(input, weight) {
this.input = input;
this.weight = weight;
}
PerceptronData.prototype.calc = function () {
var result = this.input + this.weight;
return result;
};
PerceptronData.prototype.adjust = function (error, rate) {
this.weight += (this.input * error * rate);
};
PerceptronData.prototype.print = function () {
return '(' + this.input + ', ' + this.weight + ')';
}
function Perceptron(n) {
this.data = [];//Data array [input, weight]
this.bias = new PerceptronData(1, 0);
this.rate = 0.1;//learning rate
//initial data
for (var index = 0; index < n; index++) {
this.data.push(new PerceptronData(0, 0));
}
}
//called from "guess" function in the final perceptron
Perceptron.prototype.process = function (inputs) {
var data = this.data;
if (inputs.length != data.length) {
throw "The number os inputs [" + inputs.length + "] doesn't match with the start value [" + data.length + "] of the Perceptron.";
}
var dataSum = 0;
for (var index = 0; index < data.length; index++) {
data[index].input = parseInt(inputs[index]);
dataSum += data[index].calc();
}
dataSum += this.bias.calc();
return dataSum;
};
//twick the weight for every data
Perceptron.prototype.adjust = function (value, answer) {
var data = this.data;
var error = answer - value;
for (var index = 0; index < data.length; index++) {
data[index].adjust(error, this.rate);
}
this.bias.adjust(error, this.rate);
};
Perceptron.prototype.print = function () {
var data = this.data;
var result = '';
for (var index = 0; index < data.length; index++) {
result += 'data[' + index + ']' + data[index].print() + ' > ';
}
return result + 'bias' + this.bias.print();
};
function NotPerceptron() {
Perceptron.call(this, 1);
}
NotPerceptron.prototype = Object.create(Perceptron.prototype);
NotPerceptron.prototype.guess = function (value) {
var data = this.process([value]);
//activation function
return ((data > 0) ? 1 : 0);
};
NotPerceptron.prototype.train = function (value, answer) {
var result = this.guess([value]);
this.adjust(result, answer);
};
function AndPerceptron() {
Perceptron.call(this, 2);
}
AndPerceptron.prototype = Object.create(Perceptron.prototype);
AndPerceptron.prototype.guess = function (valueA, valueB) {
var data = this.process([valueA, valueB]);
//activation function
return ((data > 0) ? 1 : 0);
};
AndPerceptron.prototype.train = function (valueA, valueB, answer) {
var result = this.guess(valueA, valueB);
this.adjust(result, answer);
};
function OrPerceptron() {
Perceptron.call(this, 2);
}
OrPerceptron.prototype = Object.create(Perceptron.prototype);
OrPerceptron.prototype.guess = function (valueA, valueB) {
var data = this.process([valueA, valueB]);
//activation function
return ((data > 0) ? 1 : 0);
};
OrPerceptron.prototype.train = function (valueA, valueB, answer) {
var result = this.guess(valueA, valueB);
this.adjust(result, answer);
};
</script>
</head>
<body>
<script type="text/javascript">
Show('Training AND...');
Show();
var and = new AndPerceptron();
var count = 0;
var total = 0;
var max = 100;
while (count < 10 && total < max) {
total++;
var a = getRandom();
var b = getRandom();
var answer = ((a === 1 && b === 1) ? 1 : 0);
and.train(a, b, answer);
a = getRandom();
b = getRandom();
answer = ((a === 1 && b === 1) ? 1 : 0);
var guess = and.guess(a, b);
if (guess === answer) {
count++;
} else {
count = 0;
}
Show(' > AND(' + a + ', ' + b + ') = ' + guess + ' > [' + and.print() + ']');
if (count == 10) {
//final test
if (and.guess(0, 0) == 1) {
count = 0;
}
if (and.guess(0, 1) == 1) {
count = 0;
}
if (and.guess(1, 0) == 1) {
count = 0;
}
if (and.guess(1, 1) == 0) {
count = 0;
}
}
}
Show();
if (total >= max) {
Show('AND training failed...');
} else {
Show('AND trained with [' + total + '] interactions. [' + and.print() + ']');
}
Show();
Show('AND(0, 0) = ' + and.guess(0, 0));
Show('AND(0, 1) = ' + and.guess(0, 1));
Show('AND(1, 0) = ' + and.guess(1, 0));
Show('AND(1, 1) = ' + and.guess(1, 1));
Show();
Show('Training OR...');
Show();
var or = new OrPerceptron();
count = 0;
total = 0;
max = 100;
while (count < 10 && total < max) {
total++;
var a = getRandom();
var b = getRandom();
var answer = ((a === 1 || b === 1) ? 1 : 0);
or.train(a, b, answer);
a = getRandom();
b = getRandom();
answer = ((a === 1 || b === 1) ? 1 : 0);
var guess = or.guess(a, b);
if (guess === answer) {
count++;
} else {
count = 0;
}
Show(' > OR(' + a + ', ' + b + ') = ' + guess + ' > [' + or.print() + ']');
if (count == 10) {
//final test
if (or.guess(0, 0) == 1) {
count = 0;
}
if (or.guess(0, 1) == 0) {
count = 0;
}
if (or.guess(1, 0) == 0) {
count = 0;
}
if (or.guess(1, 1) == 0) {
count = 0;
}
}
}
Show();
if (total >= max) {
Show('OR training failed...');
} else {
Show('OR trained with [' + total + '] interactions. [' + or.print() + ']');
}
Show();
Show('OR(0, 0) = ' + or.guess(0, 0));
Show('OR(0, 1) = ' + or.guess(0, 1));
Show('OR(1, 0) = ' + or.guess(1, 0));
Show('OR(1, 1) = ' + or.guess(1, 1));
Show();
Show('Training NOT...');
Show();
var not = new NotPerceptron();
not.rate = 0.1;
count = 0;
total = 0;
max = 100;
while (count < 10 && total < max) {
total++;
var test = getRandom();
var answer = ((test === 1) ? 0 : 1);
not.train(test, answer);
test = getRandom();
answer = ((test === 1) ? 0 : 1);
var guess = not.guess(test);
if (guess === answer) {
count++;
} else {
count = 0;
}
Show(' > NOT(' + test + ') = ' + guess + ' > [' + not.print() + ']');
if (count == 10) {
//final test
if (not.guess(0) == 0) {
count = 0;
}
if (not.guess(1) == 1) {
count = 0;
}
}
}
Show();
if (total >= max) {
Show('NOT training failed...');
} else {
Show('NOT trained with [' + total + '] interactions. [' + not.print() + ']');
}
Show();
Show('NOT(1) = ' + not.guess(1));
Show('NOT(0) = ' + not.guess(0));
</script>
</body>
</html>
在@Stanislav Kralin sugestion之后，我再次更新了这个问题，因此它显示了问题。这就是解决办法 问题在于CALC函数应该乘以输入的权重值。但我正在添加它 不幸的是，我非常关注是否应该使用sigmoid函数或其他函数，关注学习率以及线性和非线性函数，以至于我没有看到这个错误 事实上，与和以及或感知器配合良好，这确实让我走错了方向
PerceptronData.prototype.calc = function () {
//var result = this.input + this.weight;//This was wrong... :(
var result = this.input * this.weight;
return result;
};
请同时添加代码。当我回家编辑问题并发布代码时，我发现了错误。无论如何谢谢你。我已经用所有代码更新了这个问题。那么问题出在哪里？现在它工作得很好。张贴你的答案并接受它。我认为你的问题很有启发性，不应该以“一个无法再复制的问题或一个简单的印刷错误”来结束。好的，我会这么做
PerceptronData.prototype.calc = function () {
//var result = this.input + this.weight;//This was wrong... :(
var result = this.input * this.weight;
return result;
};