Classification of Breast Cancer Data Using Machine Learning Algorithms

Machine learning has become an increasingly popular subject of study over the last two decades. Different algorithms have been applied to different types of datasets including medical ones. The literature already has numerous studies that involve medical data classification on different platforms. In this study, accuracies of three different machine learning algorithms, k-Nearest Neighbors (k-NN), Naïve Bayes (NB) and Support Vector Machine (SVM), have been investigated with Weka software. Results have been generated using different appropriate parameters for each algorithm respectively. k-NN and SVM algorithms were found to be the most accurate ones with identical confusion matrices and accuracy values.