architecture. We proceed to define an upper bound on the remaining part of the parameter,
and show considerable empirical evidence that a lower bound also exists. As the size of
the ensemble increases, the upper and lower bounds converge, indicating that the optimal
parameter can be determined exactly. We describe a number of experiments with differ-
ent datasets and ensemble architectures, including the first comparisons to other popular
ensemble methods; we find NC to be a competitive technique, worthy of further application.
Finally we conclude with observations on how this investigation has impacted our under-
standing of diversity in general, and note several possible new directions that are suggested
by this work. This includes links to evolutionary computation, Mixtures of Experts, and
regularisation techniques.