Clustering Evaluation by Davies-Bouldin Index(DBI) in Cereal data using K-Means
Akhilesh Kumar Singh, Shantanu Mittal, Prashant Malhotra, Yash Vardhan Srivastava
Abstract
Cereals grains have been used as a principle ingredient of human diet for hundreds of years. Indian cereal crops provide vital nutrients and energy to the human diet. The motivation behind this research paper is to distribute the research discoveries of applying K-Means clustering, on a cereal dataset and to differentiate the outcomes found on the number of bunches to identify whether the ideal or best number of groups to be 3 or 5. This speculation is achieved by applying distinctive clustering tests (likewise reordered in the paper), and visualizations. The aforementioned resolution by doing exploratory analysis, at that point modeled fitting followed by result testing, driving us to a definite end. The language utilized for our exploration is R.