NEFCLASS for Java-new learning algorithms
Detlef D. Nauck, U. Nauck, Rudolf Kruse · 2003
Neuro-fuzzy classification approaches aim at creating fuzzy classification rules from data. Our neuro-fuzzy model NEFCLASS is able to learn fuzzy rules and fuzzy sets by simple heuristics. The aim of NEFCLASS is to quickly create interpretable fuzzy classifiers. In this paper, we present NEFCLASS-J-a new version of our approach that was written in Java and contains some additions to the learning algorithms, like the treatment of missing values, the ability to use symbolic data, automatic determination of the size of the rule base, and a new automatic pruning strategy.