Hybrid BRAINNE: Further developments in extracting symbolic disjunctive rules

摘要

A method for learning disjunctive rules using a combination of two existing neural network schemes is further explored. The hybrid network consists of two layers: an unsupervised and a supervised network. The first layer is used for ordering the inputs of training instances into clusters. Initial rules are extracted from this layer using an existing technique called Unsupervised BRAINNE. These rules are then fed into the second layer which is trained using the delta rule. The second layer is then examined to determine which clusters define the output nodes. This method is able to identify disjunctive rules directly.