Prototyping and Analyzing the Approach of Efficient Mining of Educational Data

Abstract

Data Mining is among the most important research domains in recent a year which focuses on the aspects of real world. To get patterns and predictions on the basis of the data, data mining or classification techniques can be used. Efficiency of the educational institutes, students performance and student employability are in the main focus of today’s education system. So the efficient data mining of the educational data is become very critical. The analysis of the efficient usage of techniques, to find out the pattern between student performance, employability and the educational institute’s responsibility is shown in this paper. This pattern can be found by extracting the knowledge from the educational student performance data. Using this data, different Data mining Techniques can be applied to find out the useful patterns and fill the gap between the Student Academics and Employability. This paper includes analysis on different classification techniques like decision tree algorithm, C4.5, ADTree, ID3, SVM, and compares the best performances on different aspects.