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brain.js/examples/javascript/cross-validate.js /
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| const brain = require('brain.js'); | |
| const trainingData = [ | |
| // xor data, repeating to simulate that we have a lot of data | |
| { input: [0, 1], output: [1] }, | |
| { input: [0, 0], output: [0] }, | |
| { input: [1, 1], output: [0] }, | |
| { input: [1, 0], output: [1] }, | |
| // repeat xor data to have enough to train with | |
| { input: [0, 1], output: [1] }, | |
| { input: [0, 0], output: [0] }, | |
| { input: [1, 1], output: [0] }, | |
| { input: [1, 0], output: [1] }, | |
| ]; | |
| const netOptions = { | |
| hiddenLayers: [3], | |
| }; | |
| const trainingOptions = { | |
| iterations: 20000, | |
| log: (details) => console.log(details), | |
| }; | |
| const crossValidate = new brain.CrossValidate(brain.NeuralNetwork, netOptions); | |
| const stats = crossValidate.train(trainingData, trainingOptions); | |
| console.log(stats); | |
| const net = crossValidate.toNeuralNetwork(); | |
| const result01 = net.run([0, 1]); | |
| const result00 = net.run([0, 0]); | |
| const result11 = net.run([1, 1]); | |
| const result10 = net.run([1, 0]); | |
| console.log('0 XOR 1: ', result01); // 0.987 | |
| console.log('0 XOR 0: ', result00); // 0.058 | |
| console.log('1 XOR 1: ', result11); // 0.087 | |
| console.log('1 XOR 0: ', result10); // 0.934 |