statistical significance using the likelihood ratio test. Split any node in the previous layer if the contribution of the current attribute has statistical significance. Otherwise, create a node from that node to one of the value nodes of the target variable, according to the majority rule. return the list of variables chosen to be used by the net and the net itself. External links Fuzzification and Reduction of Information-Theoretic Rule Sets in Data Mining and Computational Intelligence, A. Kandel, M. Last, and H. Bunke (Eds), Physica-Verlag, Studies in Fuzziness and Soft Computing, Vol. 68, pp. 63–93, 2001. A Comparative Study Of Artificial Neural Networks And Info Fuzzy Networks On Their Use In Software Testing Classification algorithms