[R] Training nnet in two ways, trying to understand the performance difference - with (i hope!) commented, minimal, self-contained, reproducible code

Dear all, Objective: I am trying to learn about neural networks. I want to see if i can train an artificial neural network model to discriminate between spam and nonspam emails. Problem: I created my own model (example 1 below) and got an error of about 7.7%. I created the same model using the

Re: [R] Training nnet in two ways, trying to understand the performance difference - with (i hope!) commented, minimal, self-contained, reproducible code

hmm, further investigation shows that two different fits are used. Why did nnet decide to use different fits when the data is basically the same (2 factors in nn1 and binary in nn2)? # uses an entropy fit (maximum conditional likelihood) nn1 a 57-3-1 network with 178 weights inputs: make