FORECASTING OF BREAST CANCER USING VOTING CLASSIFIER

Abstract

Breast cancer is the most diagnosed and the leading cause of death in women. among women is breast cancer. Between 1 in 8 and 1 in 12 women in the developed world will experience breast cancer throughout their lives. The risk of breast cancer is of two primary types. The first type is that a person is likely to develop breast cancer over a specified time period. The second type reflects the likelihood of a high-risk gene mutation. Earlier work has shown that it has been better to predict the risk of breast cancer by adding input into the wide-spread Gail model. The main objective is to predict analytics model to diagnose breast cancer stages of patients. The main objective of this work is to detect and analyze breast cancer. It predicts the stages of the cancer and gives as the accurate result. In this work, to investigate a dataset of medical patient records for hospital sector using machine learning technique and to identify patients having breast cancer stages from given dataset attributes. Then the accurate result is found by naive Bayesian algorithm with precision, recall, F1score.