Abstract: In this paper we are using data mining techniques for diagnosis and prognosis of cancer. Cancer is the most important cause of death for both men and women. The early detection of cancer can be helpful in curing the disease completely. So the requirement of techniques for the detection of cancer in early stage is increasing. Breast cancer is one of the leading cancers for women in developed countries including India. It is the second most common cause of cancer death in women. The high incidence of breast cancer in women has increased significantly in the last years. The malignant tumor develops when cells in the breast tissue divide and grow without the normal controls on cell death and cell division. Hence, cancer on breast tissue is called breast cancer. Worldwide, it is the most common form of cancer in females that is affecting approximately 10% of all women at some stage of their life. With early diagnosis, 97% of women survive for 5 years or more years. In this paper we present a system for diagnosis and prognosis of cancer using Classification and Association approach in Data Mining. We are using FP algorithm in Association Rule Mining (ARM) to conclude the patterns frequently found in benign and malignant patients. We are also using Decision Tree algorithm under classification to predict the possibility of cancer in context to age.

Keywords: Classification, Association, Frequent Pattern growth, Decision tree, Breast cancer, benign, malignant.