Java: Data Science Made Easy

Building the model

A MultiLayerConfiguration instance is created using a series of NeuralNetConfiguration.Builder methods. The following is the dice used. We will discuss the individual methods following the code. Note that this configuration uses two layers. The last layer uses the softmax activation function, which is used for regression analysis:

MultiLayerConfiguration conf = new NeuralNetConfiguration.Builder()         .iterations(1000)         .activation("relu")         .weightInit(WeightInit.XAVIER)         .learningRate(0.4)         .list()         .layer(0, new DenseLayer.Builder()                 .nIn(6).nOut(3)                 .build())         .layer(1, new OutputLayer                 .Builder(LossFunctions.LossFunction                         .NEGATIVELOGLIKELIHOOD)                 .activation("softmax")                 .nIn(3).nOut(4).build())  .backprop(true).pretrain(false) ...