Abstract
Cascade Correlation (CC) as a constructive algorithm for artificial neural networks stands out for solving hard classification problems. In this note we propose an extension of this technique that uses genetic algorithm for finding a good initialization point and yields improved results. The performance of our method is demonstrated on benchmark problems.
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