Priority based decision tree classifier for breast cancer detection
P. Hamsagayathri, P. Sampath · 2017
Breast cancer is invasive cancer among world's women above 35 years of age. The most common symptoms of breast cancer are lumps, change in shape/skin colour and liquid oozing out from nipple. Breast cancer mostly starts from breast tissues that are either in lobules or in milk ducts. Ductal carcinoma is the common type of breast cancer starts from milk ducts and spread across the. Women between the age group of 40-70 are mostly affected with breast cancers. Thus, effective and efficient early breast cancer detection and classification tools are required to reduce the mortality of women in the society. Classification plays an important role in breast cancer detection and used by researchers to analyze and classify the medical data. In this research work, priority based decision tree classifier algorithm has been implemented for SEER Breast cancer dataset. This paper analyzes J48 and priority based decision tree classifier algorithm for seer breast cancer dataset using WEKA software. The performance of the classifiers are evaluated and compared.