A Boolean Algebra Based Rule Extraction Algorithm That Extracts If-then Classification Rules from Threelayer Neural Networks with General Inputs

We present a Boolean algebra based algorithm to extract if-then classification rules from supervised learning feedforward neural networks to solve the black-box problem of the decision process of the neural networks. This algorithm is called the BAB-G rule extraction algorithm, which stands for Boolean Algebra Based for General inputs. According to the concept of discretizing continuous hidden neuron activation values, we present the BAB-G rule extraction algorithm, which can be applied to threelayer feedforward neural networks with discrete, continuous, or mixed inputs. The antecedent parts of the if-then rules obtained from this algorithm are slanting hyperplanes. If there are n-kind of different classes, we could find n-1 distinct hyperplanes. During the rule extraction procedure, redundant hidden neurons can be removed without affecting the functionality of the neural networks. By representing each interval as a single bit, we can interpret the training of neural networks as a computation involving dynamic bits. Some empirical results on the data sets from the UCI repository of machine learning database are given for comparing our rule extraction algorithm and C5.0 decision tree algorithm. For these datasets, statistical hypothesis tests show that the rules obtained from our algorithm achieve the same classification accuracy as the neural networks. Moreover, our rules are better than the C5.0 decision tree both on comprehensibility and on accuracy for these datasets. Supplementary Material File (babg.2025.02.17.pdf) - Download - 1.11 MB Information & Authors Information Version history Copyright This work is licensed under a Non Exclusive No Reuse License.

Authors Metrics & Citations Metrics Article Usage 180views 105downloads Citations Download citation Chun-Kai Hwang. A Boolean Algebra Based Rule Extraction Algorithm That Extracts If-then Classification Rules from Threelayer Neural Networks with General Inputs. Authorea. 18 February 2025. DOI: https://doi.org/10.22541/au.173990736.62275159/v1 DOI: https://doi.org/10.22541/au.173990736.62275159/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu.