Usage of association rules and classification techniques in knowledge extraction of diabetes

This research paper uses association rules and classification techniques to extract undiscovered information of diabetes. Previous phase of this research included the preliminary results of some undiscovered decision factors and side effects of diabetes, by considering diabetes type 1 and type 2 patients' data set. Advanced and reliable data mining techniques are used throughout this research to the discovery of unseen and useful information. This phase of the research describes the application of classification techniques to evaluate the results generated from the association rules. Some interesting information of diabetes was identified at the end of this research, which proved the results generated in phase 1, from the data mining domain.