Graph Theory Applications in Machine Learning

Graph theory is the Branch of Discrete mathematics which plays a key role in Machine Learning and Data Science. Graph Theory in Machine Learning states to the application of mathematical structures known as graphs to model pairwise relations between objects in machine learning. A graph in this framework is a set of objects, called nodes, connected by links, known as edges. Each edge may be directed or undirected. In mathematics, graph theory is one of the important fields used in structural models. This paper explores the applications of Graph theory and various types of graphs in Machine Learning. The paper also discusses the advantages and various types of graph theory Algorithms which are used in Machine learning.