More work on getting logistic regression to agree with neural nets.
Although the methods agree we don't appear to be converging to what I
expect (the separating hyperplane should be at roughly 0.5 as given by
the logistic regression) so I am going to start over from a known
working piece of code.
Now we get a reasonable result for the estimated parameters using
logistic regression with sum of squares cost (they give the same
result as log likelihood but they are not the same). We can probably
delete redux but let's leave it for a while.
Our neural net now converges to the same values as we get using
logistic regression. Let us capture this before tidying up.