Object Oriented K-Means clustering using Eigen Decomposition for student data

Data clustering [1] is the process of forming classes or groups of similar data objects. The real time data objects are either multi-dimensional [4] or high dimensional [3]. Grouping these high dimensional data objects requires a lot of computational effort, time and space. To remove these hurdles from clustering of high dimensional data, the proposed work uses Eigen decomposition for dimensionality reduction, and then k-means is implemented through object oriented [2] programming on student's marks data. The experimental results show how Eigen value decomposition and object oriented implementation brings novelty to clustering process.