Package Exports
- mlearningjs
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Readme
#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.