KMST+: A K-means++-based minimum spanning tree algorithm

Abstract

There are a number of algorithms that have been proposed in the graph theory literature to compute the minimum spanning tree of a given graph. These include the famous Prim’s and Kruskal’s algorithm, among others. The main drawback of these algorithms is their greedy nature, which means they cannot be applied to large datasets. In 2015, Zhong et al. proposed a fast MST (FMST) algorithm framework that uses K-means to find the MST with a reduced complexity of O(N1.5). In this paper, we have introduced an improved version of the FMST algorithm by using K-means++ to further increase the efficiency of the FMST algorithm. The use of K-means++ instead of K-means results in lesser complexity, faster convergence, and more accurate results during the clustering step which improves the accuracy of the MST formed.