Modifications of K-Means Algorithm and its Execution in Real Life Data: A Comparative Study

Abstract

K-means algorithm and its various modifications focused on real-world applications in engineering and science. It shows a wide-ranging procedure and some familiar and some lesser-known changes. The basic structure of the K-means method has been shown to enable prototype initialization and cluster analysis with implicitly defined detachment measures. It also describes a specific application of k-means clustering for real data. The key goal of this effort is to find the importance of modifications in K-means algorithm. We will discuss about the initialization and distance-based modifications of K-means algorithm. Finally, we will conclude that which kind of modification provides better result by clustering accuracy.