Rule Induction By Apriori Algorithm Using Breast Cancer Data

The amount of data, increasing together with the technology, has brought the concept of “data warehouse” in every field of life. Data Mining is a set of approaches analyzing these data warehouses formed by very large data sets and allows to gather useful information. One of the fields where the amount of data is large and getting larger everyday is the health sector. Many personal and medical data belonging to thousands of patients are recorded and stored. However, small part of these data can be analyzed and the remaining part may not be helpful to obtain useful information. The data in warehouses must be analyzed to improve the methods for hospital management systems, treatment and health care systems to reduce the costs. Since analyzing large data sets using classical statistical methods is difficult, various data mining methods have been developed and these methods have become more feasible with the help of certain softwares. Association rule is an important datamining task to find hidden patterns between the variables and used recently in the field of healthcare. In this study, we have calculated the support and confidence of the associations in data set. APRIORI algorithm have been applied onto the retrospectively obtained breast cancer data belonging to Oncology Hospital of Meram Faculty of Medicine.