我刚刚学会训练brain.js network并且正在玩它。然后我很想知道是否有可能反过来 - 预测输出的输入?
这是我的代码
C1 C2
1 (null)
但是如果我愿意的话
const brain = require('brain.js');
const network = new brain.NeuralNetwork();
/*
network.train([
{ input: { doseA: 0 }, output: { indicatorA: 0 } },
{ input: { doseA: 0.1 }, output: { indicatorA: 0.02 } },
{ input: { doseA: 0.2 }, output: { indicatorA: 0.04 } },
{ input: { doseA: 0.3 }, output: { indicatorA: 0.06 } },
{ input: { doseA: 0.4 }, output: { indicatorA: 0.08 } },
{ input: { doseA: 0.5 }, output: { indicatorA: 0.10 } },
{ input: { doseA: 0.6 }, output: { indicatorA: 0.12 } },
{ input: { doseA: 0.7 }, output: { indicatorA: 0.14 } },
], {
iterations: 1e6,
errorThresh: 0.00001
});
*/
network.fromJSON({"sizes":[1,3,1],"layers":[{"doseA":{}},{"0":{"bias":-0.7720749378204346,"weights":{"doseA":-6.819720268249512}},"1":{"bias":0.2317514568567276,"weights":{"doseA":-1.4340121746063232}},"2":{"bias":-0.34450986981391907,"weights":{"doseA":-2.9449453353881836}}},{"indicatorA":{"bias":-1.0124520063400269,"weights":{"0":-5.02399206161499,"1":-1.69333016872406,"2":-3.1710503101348877}}}],"outputLookup":true,"inputLookup":true,"activation":"sigmoid","trainOpts":{"iterations":1000000,"errorThresh":0.00001,"log":false,"logPeriod":10,"learningRate":0.3,"momentum":0.1,"callbackPeriod":10}})
const result = network.run({ doseA: 0.35 });
console.log(result);
// { indicatorA: 0.06978786736726761 }
并获得network.run({ indicatorA: 0.07 })
?
我是否被迫再次训练{ doseA: 0.35 }
,但已切换network
和input
?或者有办法扭转它吗?
答案 0 :(得分:1)
绝对有一个实用程序可以执行此操作:https://github.com/BrainJS/brain.retro.js
如果有更多的兴趣,我还可以使用查询实用程序,它使您可以执行一些非常有趣的mongo样式查询:https://github.com/BrainJS/brain.retro.js/blob/master/query.js