The Machine Learning based Optimized Prediction Method for Breast Cancer Detection

Breast Cancer is the most prevalent form of cancer and significant reason for high mortality rates among women. Manual diagnosis of this disease requires long hours & specialists. Therefore an Automated breast cancer diagnosis has been developed to reduce the time taken for diagnosis and decreases the spread of cancer. This paper presents a comparative study of four machine learning algorithms namely Logistic Regression, SVM, KNN and Naive Bayes by calculating their classification accuracy, sensitivity, specificity and other parameters. The different hyper-parameters used for different ML algorithms were manually assigned. Among all algorithms, SVM performed better with the accuracy of about 98.24%.