Machine Learning with R Cookbook - Second Edition

How it works...

Similar to other classification methods, one can also predict labels based on the neural networks trained by nnet. First, we use the predict function to generate the predicted labels based on a testing dataset, testset. Within the predict function, we specify the type argument to the class, so the output will be class labels instead of a probability matrix. Next, we use the table function to generate a classification table based on predicted labels and labels written in the testing dataset. Finally, as we have created the classification table, we can employ a confusion matrix from the caret package to measure the prediction performance of the trained neural network.