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Classifying Educational Data Using Support Vector Machines: A Supervised Data Mining Technique

Affiliations

  • Department of Computer Science, Himachal Pradesh University, Gyan-Path, Summer-Hill, Shimla - 171005, Himachal Pradesh, India

Abstract


With increase in Educational Institutions there is increase in new trends which results in large data. The data is unstructured which need to be transformed into structured form and to find out meaningful information, effective Mining Tools are required. Educational Data Mining helps in facilitating utilization of resources related to student performance, predicting placement results and finding new educational trends. In this paper placement data of students has been taken and classification approach using SVM is followed on training data for predicting results which not only helps educational institutions to improve student placements from extracted knowledge as well enhances the competitive advantage and decision making by applying data mining techniques. SVM is a supervised learning and effective data mining technique to train the data for pattern recognition and predictions.

Keywords

Classification, Data Mining, Educational Data Mining, Predicting, Support Vector Machines.

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References


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