Linguistic Knowledge Extraction from Neural Networks Using Maximum Weight and Frequency Data Representation

This paper presents a method of linguistic rule extraction from neural networks nodes pruning using frequency interval data representation. The method composes of two steps which are 1) neural networks nodes pruning by analysis on the maximum weight and 2) linguistic rule extraction using frequency interval data representation. The study has tested with the benchmark data sets such as heart disease, Wisconsin breast cancer, Pima Indians diabetes, and electrocardiography data set of heart disease patients from hospitals in Thailand. The study found that the linguistic rules received had high accuracy and easy to understand. The number of rules and the number of conjunction of conditions were small and the training time was also decreased