preceding sections list only a few of the many algorithms that have been proposed.
The list is not exhaustive by any means so we encourage the reader to explore
further for a more complete survey. Genetic algorithms, for example, have been
proposed to both generate the network structure and find the appropriate weights.
Some of the weight initialization techniques mentioned in chapter 7 construct networks based on solutions provided by
other method, for example, decision trees (section 7.2.5) or rule-based knowledge (section 7.2.6). A polynomial time algorithm using clustering
and linear programming techniques to generate classifier networks is described
in . Projection pursuit regression , , a well-known statistical procedure, creates a system
similar to a single-hidden-layer network with a linear output node. It is constructive
in the sense that it adds projection directions (corresponding to hidden units)
sequentially until the error is sufficiently small.