Neural network attempts addition

neural-add.js

const Synaptic = require('synaptic');

const NUM_INPUTS = 2;
const HIDDEN = 1;
const NUM_OUTPUTS = 1;
const network = new Synaptic.Architect.Perceptron(
	NUM_INPUTS,
	HIDDEN,
	NUM_OUTPUTS
);
const trainingSet = [
	{ input: [0.2, 0.2], output: [0.4] },
	{ input: [0.1, 0.3], output: [0.4] },
	{ input: [0.3, 0.15], output: [0.45] },
	{ input: [0.2, 0.25], output: [0.45] },
	{ input: [0.01, 0.1], output: [0.11] },
	{ input: [0.8, 0.01], output: [0.81] },
	{ input: [0.9, 0.1], output: [1] },
	{ input: [0.01, 0.99], output: [1] },
	{ input: [0.6, 0.4], output: [1] },
	{ input: [0.45, 0.5], output: [0.95] },
	{ input: [0.47, 0.23], output: [0.7] },
	{ input: [0.4, 0.3], output: [0.7] },
	{ input: [0.33, 0.3], output: [0.63] },
	{ input: [0.42, 0.1], output: [0.52] },
	{ input: [0, 0], output: [0] },
	{ input: [1, 0], output: [1] }
];
const trainer = new Synaptic.Trainer(network);
trainer.train(trainingSet, {
	iterations: 30000,
	shuffle: true,
	log: 1000
});

let input = [0.5, 0.45];
let prec = 1e3;
console.log(Math.round(network.activate(input) * prec) / prec);