得到很多结果是正常行为吗？

Question

我制作了一个使用神经网络的应用程序，当我在“分类”按钮中提供它时，它返回的结果有些不同（47％，50％，51％...），因为我使用的所有分类都相同数据，但得到不同的结果，这正常吗？

我使用了这个库https://github.com/cazala/synaptic/wiki/Neurons，这是分类的代码：

const synaptic = require('synaptic');
var A = new synaptic.Neuron();
var B = new synaptic.Neuron();
A.project(B);

A.activate(0.5); // 0.5
B.activate(); // 0.32, 0.53, 0.47, 0.48

是功能激活的行为吗？反向传播？

编辑1：更多其他示例：

const synaptic = require('synaptic'); // this line is not needed in the browser


var network = new synaptic.Architect.Perceptron(2, 4, 4, 1);

var trainingSet = [
    {
        input: [-1.758, 0.74, -0.921, -0.281, -0.838, -0.445, -0.976, -0.274, -0.815, -0.257, -1.205, -0.174],
        output: [1]
    },
    {input: [0.166, 0.53, -1.043, -0.844, -0.61, -0.145, -0.349, -0.359, -0.918, 0.002, -0.463, 0.211], output: [1]},
    {input: [-0.54, 0.31, -1.024, -0.674, -0.686, 0.034, -1.05, 0.33, -1.022, -0.278, -0.704, 0.075], output: [1]},
    {input: [-0.45, 0.891, -1.027, -0.284, -0.593, -0.264, -1.044, 0.425, -1.009, -0.245, -0.699, 0.238], output: [1]},
    {
        input: [-0.502, 0.503, -0.898, -0.122, -0.133, -0.718, -1.075, 1.295, -1.032, -0.468, -0.731, -0.194],
        output: [1]
    },
    {input: [-0.49, 0.681, -0.801, -0.476, -0.554, -0.052, -1.064, 1.48, -0.956, -0.101, -0.621, 0.075], output: [1]},
    {input: [-0.453, 0.52, -0.893, -0.353, -0.552, -0.689, -1.014, 1.135, -1.066, -0.208, -0.779, -0.281], output: [1]},
    {input: [-1.578, 1.767, 1.88, 2.677, 3.206, -0.575, 1.454, -0.009, 1.217, 0.665, 2.367, -0.089], output: [0]},
    {input: [1.089, -1.369, 1.161, 1.51, 0.977, 3.213, 0.875, 1.36, 0.915, 3.182, 0.135, 3.295], output: [0]},
    {input: [0.597, -0.62, 1.142, -0.79, 0.108, -0.493, 0.811, -1.51, 1.391, -0.562, 1.783, -0.27], output: [0]},
    {input: [0.346, -1.053, 0.444, -1.043, -0.277, -0.888, 1.612, -0.924, 1.141, -1.354, -0.368, -1.005], output: [0]},
    {input: [0.863, -1.678, 0.648, 0.586, 0.207, 0.923, 0.38, -1.109, 1.072, -0.235, -0.015, -0.299], output: [0]},
    {input: [2.1, 0.173, 0.741, 0.676, -0.309, 0.337, 0.508, -0.454, 0.456, 0.537, 0.762, -0.317], output: [0]},
    {input: [0.61, -1.396, 0.59, -0.58, 0.056, -0.235, 0.933, -1.384, 0.626, -0.675, 0.541, -1.262], output: [0]}
];

let intent =
    [[[-1.885, 1.368, -0.794, -0.945, -0.841, -0.394],[ -1.015, 1.12, -0.823, -0.031, -1.356, -0.248]],
    [[-1.903, 0.114, -0.851, -1.075, -0.84, -0.851],[ -0.975, -0.099, -0.803, -0.15, NaN, NaN]],
    [[-1.886, 0.472, -0.891, -0.819, -0.838, -0.487],[ -0.912, -0.204, -0.753, -0.767, -1.238, -0.424]],
    [[-1.865, 1.145, -0.882, -0.588, -0.86, -0.304],[ -0.954, 0.125, -0.763, -1.179, -1.353, -0.5]],
    [[-1.856, 1.124, -0.913, -0.335, -0.86, 0.252],[ -1.022, 0.5, -1.15, 0.723, -1.315, -1.262]],
    [[-1.705, 0.729, -0.092, 0.206, -0.858, -0.519],[-0.958, 0.225, -0.801, -0.229, -1.449, -0.386]],
    [[-1.855, 1.344, -0.894, -0.309, 0.366, -0.134],[ -0.661, 0.965, -0.505, -1.127, -1.383, -0.161]],
    [[-1.861, 0.317, -0.797, -0.295, -0.836, -0.291],[ -0.976, 0.79, -0.819, -0.168, -1.334, -0.058]],
    [[-1.857, 1.083, -0.931, -0.653, -0.831, -0.264],[ -1.034, 0.225, -0.759, 0.1, -1.342, 0.075]],
    [[-1.882, 0.369, -0.926, -0.562, -0.883, 0.31],[ -0.965, 0.465, -0.759, -0.48, NaN, NaN]],
    [[-1.873, 0.86, -0.962, -0.483, -0.867, 0.095],[ -0.982, -0.039, -0.862, -0.529, -1.223, -1.025]],
    [[-1.895, 0.468, -0.964, -0.906, -0.861, 0.353],[ -0.971, -0.219, -0.796, -0.516, -1.395, -0.301]],
    [[-1.822, 1.159, -0.96, -0.707, -0.838, -0.124],[ -0.979, 0.025, -0.854, -0.101, -1.352, -0.558]],
    [[-1.836, 0.43, -0.95, -0.364, -0.874, 0.082],[ -1.037, 0.885, -0.863, -0.712, -1.325, -0.563]],
    [[-1.858, 1.324, -0.892, 0.109, -0.889, 0.079],[ -0.997, 0.1, -0.949, 0.369, -1.246, -0.652]],
    [[-1.836, 0.925, -0.889, -0.338, -0.833, -0.241],[ -1.072, 0.19, -0.908, -0.138, -1.26, -0.447]],
    [[-1.834, 1.41, -0.881, -0.259, -0.839, 0.361],[ 0.863, 0.515, 0.8, -0.306, -1.344, 0.477]],
    [[-1.836, 0.956, -0.892, -0.385, -0.894, 0.109],[ -1.015, 0.03, -0.828, -0.565, -1.343, -0.523]],
    [[-1.892, 0.736, -0.914, -0.324, -0.827, -0.18],[ -1.04, 0.26, -0.848, -0.425, -1.379, -0.317]],
    [[-1.89, 0.554, -0.797, -0.057, -0.235, 1.358],[ -0.716, 1, -0.53, -0.413, -1.269, -0.518]]]






function ads() {
    var trainer = new synaptic.Trainer(network);

    let errors = [];
    trainer.train(trainingSet, {
        rate: 0.005,//0.003
        iterations: 20000,
        error: 0.0001,//0.005
        schedule: {
            every: 100,
            do: function (data) {
                errors.push(data.error);
            }
        }
    });
}
let predict = [];
let learningRate = 0.003;

for (let i = 0; i < intent.length; i++) {
    let parcial=[];
    for (let j = 0; j < intent[i].length; j++) {
        ads();
        const predictedLabel = network.activate(intent[i][j]);
        parcial.push(predictedLabel);
    }
    predict.push(parcial);
}
console.log(predict);