Rules Extraction by Constructive Learning of Neural Networks and Hidden-Unit Clustering

摘要

Classification is one of the most important consideration of the data mining problems. The measure of success in a classification problem is the accuracy of the classifier, usually defined by the percentage of correct classifications. Recently, neural networks have been thought as one approach to solve this problem, but the difficulty is that the classification rules generated by neural networks are not explicitly represented in the human understanding form.