R Deep Learning Cookbook

How it works...

In steps 1 through 3, we extract the true and predicted test class labels and create a confusion matrix. The following image shows the confusion matrix of the current test predictions:

The test accuracy post 700 training iterations is only ~51% and can be further improved by increasing the number of iterations, increasing the batch size, configuring layer parameters such as the number of convolution layers (used 2), types of activation functions (used ReLU), number of fully connected layers (used two), optimization objective function (used accuracy), pooling (used max 2 x 2), dropout probability, and many others.

Step 4 is ...