Dann

npm i dannjs

const { Dann } = require('dannjs');

const nn = new Dann(4, 2);
nn.addHiddenLayer(6, 'leakyReLU');
nn.addHiddenLayer(6, 'leakyReLU');
nn.outputActivation('tanH');
nn.makeWeights();
nn.lr = 0.0001;
nn.log({details:true});

//XOR 2 inputs, 1 output
const dataset = [
    {
        input: [0, 0],
        output: [0]
    },
    {
        input: [1, 0],
        output: [1]
    },
    {
        input: [0, 1],
        output: [1]
    },
    {
        input: [1, 1],
        output: [0]
    }
];

//train 1 epoch
for (data of dataset) {
    nn.backpropagate(data.input, data.output);
    console.log(nn.loss);
}

const populationSize = 1000;
let newGeneration = [];

for (let i = 0; i < populationSize; i++) {

    // parentNN would be the best nn from past generation.
    const childNN = parentNN;
    childNN.mutateRandom(0.01, 0.65);

    newGeneration.push(childNN);
}

let strfunc = nn.toFunction();
console.log(strfunc);

let json = nn.toJSON();
console.log(json);

npm i dannjs