Breast Cancer Prediction system

Abstract

Breast cancer became the major source of mortality between women. The accessibility of healthcare datasets and data analysis promote the researchers to apply study in extracting unknown pattern from healthcare datasets. The intention of this study is to design a prediction system that can predict the incidence of the breast cancer at early stage by analyzing smallest set of attributes that has been selected from the clinical dataset. Wisconsin breast cancer dataset (WBCD) have been used to conduct the proposed experiment. The potential of the proposed method is obtained using classification accuracy which was obtained by comparing actual to predicted values. The outcome confirms that the maximum classification accuracy (99.28%) is achieved for this study.