Detection of Breast Cancer Using Machine Learning Algorithms
Prithviraj Jain · International Journal for Research in Applied Science and Engineering Technology · 2022
Abstract: Breast Cancer is one of the most frequently occurring cancers in women. Cancer rates are increasing in almost every region around the world. Early detection of cancer is the most efficient way to prevent the deaths caused due to it. Currently, the most commonly used tests for the detection of cancer are Mammograms, Breast Ultrasound and Breast MRI. These techniques have their own disadvantages which include the risk of false detection or no guarantee that all cancers will be detected. It is crucial to use alternative methods that are easier to implement and produce more reliable results. The solution is to use various Machine Learning algorithms to overcome the disadvantages of traditional techniques. This paper aims to propose a prediction model using Machine Learning classifier algorithms like Naïve Bayes (NB), Logistic Regression (LR), K-Nearest Neighbor (KNN), and Support Vector Machine (SVM). The performance of the various classifiers is compared in terms of accuracy, precision, and recall and the best classifier for the detection of cancer.