mlearningjs

#mlearning.js

A machine learning library written in JavaScript.

#Usage

First you have to initialize a network

var Network = require('mlearning').Network;

var myNetwork = new Network(50, 250);

The first argument is the size of the input vector. The second number is the size of the batches during training.

Next you can create your network

myNetwork.addLayer(5000, 0.01);
myNetwork.addReLU();
myNetwork.addLayer(2, 0.1);
myNetwork.addReLU();
myNetwork.addSoftmax();
myNetwork.useCrossEntropyLoss();

The above code creates a Deep Neural Network with a hidden layer of size 5000. The output is of size 2. In between each layer is a rectifier linear unit non-linearity. The final layer is a softmax. The loss function the network will use is the cross entropy loss function.

Finally, we can train the network

myNetwork.train(100000, (batchSize) => {
    return {
        X: someInputMatrix,
        Y: someOutputMatrix
    };
}

The network will train for the number of iterations stated using the second parameter as the function to generate the input and expected values.