Clustering Academies: An Integrated Approach using Genetic Algorithm and Data Mining

Abstract

Educational Data Mining deals with developing methods to explore unique types of data in educational settings by applying a combination of approaches such as data mining, statistical and machine learning to get viable information. The objective of this paper is to help prospective students in selecting good academy during their enrollment to degree courses. In this paper, an integrated approach consisting of evolutionary approach i.e. genetic algorithm for preprocessing the data of 75 academies of Bangalore and data mining approach i.e. k-means for clustering the academies is used. Thus the cluster obtained as result will consist of academies that will be ranked as Excellent [E], Good [G], Average [A] and [Poor] according to the considered attributes. This work will help the prospective students in selecting the best academy during admission.