Comparison of Different Classification Techniques for Educational Data

Data mining has been used extensively in various domains of application for prediction or classification. Data mining improves the productivity of its analysts tremendously by transforming their voluminous, unmanageable and prone to ignorable information into usable pieces of knowledge and has witnessed a great acceptance in scientific, bioinformatics and business domains. However, for education field there is still a lot to be done, especially there is plentiful research to be done as far as Indian Universities are concerned. Educational Data Mining is a promising discipline, concerned with developing techniques for exploring the unique types of educational data and using those techniques to better understand students' strengths and weaknesses. In this paper, the educational database of students undergoing higher education has been mined and various classification techniques have been compared so as to investigate the students' placement in software organizations, using real data from the students of a Delhi state university's affiliates.