A SURVEY PAPER ON THE CLASSIFICATION TECHNIQUES IN EDUCATIONAL DATA MINING USING NEURAL NETWORK
Author’s Name : Dipali Singh
Volume 04 Issue 04 Year 2017 ISSN No: 2349-3828 Page no: 1-4
Due to increasing interest in data mining and educational system, educational data mining is the emerging topic for research community. educational data mining means to extract the hidden knowledge from large repositories of data with the use of technique and tools. educational data mining develops new methods to discover knowledge from educational database and used for decision making in educational system. The various techniques of data mining like classification. clustering can be applied to bring out hidden knowledge from the educational data. In this paper, we focus on the educational data mining and classification techniques. In this study we analyze attributes for the prediction of student’s behavior and academic performance by using WEKA open source data mining tool and various classification methods like decision trees, C4.5 algorithm, ID3 algorithm etc.
Educational Data Mining, Classification, Analysis, WEKA
- Kumar S. Anupama and N. vijaylaxmi M.2011 Efficiency of Decision trees in predicting Student’s Academic performance.
- L. Ramanathan, Dhanda S. and D. S. Kumar 2013 Predicting Student’s Performance using Modified ID3 Algorithm
- Pal A. kumar and Pal S. 2013 Classification Model of Prediction for Placement of Students
- Cheewaprakobkit P.2013 Study of Factors Analysis Affecting Academic Achievement of Undergraduate Students in International Program
- Bresfelean V. Paul 2007 Analysis and Predictions on Student’s Behaviour using Decision Trees in Weka Environment Babes Bolyai University
- Baker Ryan S.J.d. Data mining for education Carnegie Mellon University