Comparative study of SVM and KNN for tumor prediction

Abstract

Classification algorithms have played a vital role in the field of machine learning and data science. They cannot be downplayed. There are several variants of classification algorithms. In this paper, we compare KNN (K- nearest neighbors) and SVM (Support Vector Machine) algorithms. The attributes of both the algorithms are conferred. The benefits and drawbacks of each of these algorithms are assessed and finally arrive at a conclusion on which one has higher efficiency. We shall examine the efficiency of each algorithm based on their learning curve, comparing their accuracy on tumor prediction.