Breast Cancer Prediction Using Machine Learning Approaches

Abstract

The main aspect of this study is to evaluate the different Machine learning classifiers performance for prediction of breast cancer disease.In this work, we have used six supervised classification techniques for the classification of breast cancer disease. For example: SVM, NB, KNN, RF, DT and LR were used for early prediction of breast cancer. Therefore, we evaluated the breast cancer dataset through sensitivity, specificity, f 1 measure and total accuracy. The prediction performance of breast cancer analysis shows that SVM obtained the uppermost performance with utmost classification accuracy of 97.07%. Whereas, NB and RF has achieved the second highest accuracy by prediction.Our findings can be used to help reduce the occurrence of the breast cancer disease through developing a machine learning based predictive system for early prediction.