A fuzzy neural network for data mining: dealing with the problem of small disjuncts

In today´s information age, data mining, i.e., extracting useful patterns or relationships from vast amount of data, has became increasingly important. Decision trees are currently the most popular tools for data mining. Despite many advantages in this approach, same aspects require improvements. A notable problem is known as the problem of small disjuncts, where the induced rules that cover a small amount of training cases often have high error rates. The purpose of the present paper is to show that a dynamically constructed recurrent fuzzy neural network can deal effectively with this problem