Machine Learning in Java - Second Edition

Building a single-layer regression model

Let's start by building a single-layer regression model based on the softmax activation function, as shown in the following diagram. As we have a single layer, Input to the neural network will be all the figure pixels, that is, 28 x 28 = 748 neurons. The number of Output neurons is 10, one for each digit. The network layers are fully connected, as shown in the following diagram:

A neural network is defined through a NeuralNetConfiguration.Builder() object as follows:

MultiLayerConfiguration conf = new NeuralNetConfiguration.Builder() 

We will define the parameters for gradient search in order to perform ...