A Machine Learning based Approach for Breast Cancer Prediction
Mayank Agrawal, Vinod Jain · 2022 International Conference on Automation, Computing and Renewable Systems (ICACRS) · 2022
Breast cancer is currently a rather frequent kind of cancer. Recently, it has been observed in many women, and it has been responsible for several fatalities. In order to prevent this terrible disease, it is important to forecast the likelihood of cancer in its earliest stages. Machine learning is a novel AI approach whose potential for cancer prediction has not yet been fully understood. In this work, the ability of machine learning classifiers is employed to forecast breast cancer. Machine learning algorithms applied in this work to predict the breast cancer are Support Vector Classifier, Random Forest Classifier, KNN Classifier, and Logistic Regression Classifier. The experiment's findings show that Logistic Regression outperforms the other three prediction methods.