ASSOCIATION RULE FOR CLASSIFICATION OF BREAST CANCER PATIENTS

Abstract

WOS: 000416216800009Data mining studies carried out on medical databases are very important in order to make an effective medical diagnosis. The purpose of data mining is to extract information from databases, to define clear and understandable patterns. In this study, an approach was presented to generate association rules on the data of breast cancer patients. Apriori algorithm is used for the extract of the rules. Apriori algorithm is usually used for the market - basket analysis. Apriori algorithm is used to determine customer shopping profiles or to campaign, in order to catch the shopping patterns. In this study, apriori algorithm was used in the extraction of the rules within the medical data. UC-Irvine archive repository of machine learning datasets [1] - Breast Cancer dataset has been studied. This dataset, including 9 attribute and 1 class atribute. It consists of records of 286 patients with 10 attributes. The study was carried out by using the Weka data mining program