Automated Breast Cancer Prediction System-Based On Machine Learning Algorithm Approach

The breast cancer is a common disease prevalent among the women all over the globe. The researchers are trying to find a better diagnosis method to detect the disease at the early stage. A system known as computer aided diagnosis – based on Artificial Intelligence (AI) technique is proposed to diagnose the breast cancer disease at the faster rate. Ridge Regression (RR) a Machine learning (ML) model has been selected for the expectation of the disease detection at the early stage on the sample breast cancer dataset. The method will help the medical practitioners to take decision on the disease swiftly. The breast cancer dataset consists of two classes of disease: Benign and Malignant. It can be seen as a problem of putting things into two groups. The classifier was trained on the sample dataset of two classes (Binary Classification). After training the classifier properly, the classifier's performance was tested on the test dataset. It was discovered that the way something works or its effectiveness, the empirical results indicate that the Ridge regression classifier outperforms alternative classification methods, showcasing its efficacy in achieving higher classification accuracy and reliability in the classification of Benign and Malignant.