Performance Evaluation of Data Mining Algorithm on Electronic Health Record of Diabetic Patients

Abstract

Data mining is a process of finding interesting patterns from large databases. One of the important application areas of data mining is health-care sector. In health care, it is not only providing useful information to health-care professionals but it also provides for health insurance companies. Using these techniques, many diseases can be predicted at an earlier stage which gives betterment life for human being. In our research work, we have collected an electronic health record database for a disease of diabetic patients. Every day, the volume of health-care data is increasing. Using data mining techniques extract the knowledge from this enormous database efficiently. Many algorithms are available in data mining. We have used classification algorithms such as One R, Zero R, J48, random forest, and linear discriminate analysis. The performance evaluation of classifiers can be analyzed through confusion matrix and in terms of precision, recall, and error rate.