MultiLayerConfiguration conf = new NeuralNetConfiguration.Builder()
                .seed(12345)
                .iterations(1)
                .weightInit(WeightInit.XAVIER)
                .updater(Updater.ADAGRAD) // using default momentum 0.9?
                .activation(Activation.RELU)
                .optimizationAlgo(OptimizationAlgorithm.STOCHASTIC_GRADIENT_DESCENT)
                .learningRate(0.05)
                .regularization(true).l2(0.0001)
                .list()
                .layer(0, new DenseLayer.Builder().nOut(10).build())
                .layer(1, new DenseLayer.Builder().nOut(10).build())
                .layer(2, new DenseLayer.Builder().nOut(10).build())
                .layer(3, new OutputLayer.Builder().lossFunction(LossFunctions.LossFunction.MSE).nOut(1).build())
                .setInputType(InputType.recurrent(3)) // makes all layers have .nIn(3)
                .pretrain(false)
                .backprop(true)
                .build()