Neural Networks and Rough Sets: A comparative study on data classification

This paper addresses a contrastive study between Neural Networks and Rough Sets on data classification. The experiments were carried out using the Iris database, of public domain, to evaluate the classification. The confusion matrix method was used to evaluate the performance of these classifiers. With these contrastive experiments, we investigated the capacity of each classifier for application in a potential application on knowledge extraction in databases. In this experiment the results indicate that the Neural Networks classifier, except SLP, presents significant superiority on Rough Sets classifiers.