NEFCLASS-J - A JAVA-Based Soft Computing Tool

Neuro-fuzzy classification systems offer means to obtain fuzzy classification rules by a learning algorithm. It is usually no problem to find a suitable fuzzy classifier by learning from data; however, it can be hard to obtain a classifier that can be interpreted conveniently. There is usually a trade-off between accuracy and readability. In this paper we discuss NEFCLASS – our neuro-fuzzy approach for classification problems – and its most recent JAVA implementation NEFCLASS-J. We show how a comprehensible fuzzy classifier can be obtained by a learning process and how automatic strategies for pruning rules and variables from a trained classifier can enhance its interpretability.