An Optimized Ensemble Model for Early Breast Cancer Prediction

Abstract

Breast cancer is one of the pronounce cancer among females, following lung cancer despite constant efforts by developed countries. However, if the diagnosis is made in the early non-metastatic stage, it can be cured in 70- 80% of cases. Therefore, it is vitally important to detect cancer and predict the stage as accurately as possible. We proposed an optimal model to predict the chance of early breast cancer inheritance and to undergo further treatment as soon as possible. The features are trained using classification machine learning The performance of these traditional machine learning algorithms has the potential to improve. There is room for correction, so our aim is to optimize the prediction model to improve the performance. The results obtained with our optimized ensemble algorithm are quite satisfactory and improved with an accuracy of 83.07%.