Feedforward Bayesian neural network and continuous attributes
Igor Kononenko · 1991
Two methods for dealing with continuous attributes are proposed. The fuzzy learning method assumes fuzzy bounds of a continuous attribute during learning and the fuzzy classification method assumes fuzzy bounds during classification. The performance was tested on two medical diagnostic problems. The results obtained show that the proposed methods for dealing with continuous attributes perform better than the splitting of the attribute's values with exact bounds.>