Total views : 362
Classifying Educational Data Using Support Vector Machines: A Supervised Data Mining Technique
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.
Classification, Data Mining, Educational Data Mining, Predicting, Support Vector Machines.
- El-Halees Alaa. Mining Students Data to Analyse Learning Behaviour: A Case Study: Available online from: https://uqu.edu.sa/files2/tiny_mce/plugins/filemanager/files/30/papers/f158.pdf.
- Ertekin S_eyda. Learning in extreme conditions: online and active learning with massive, imbalanced and noisy data; A Dissertation.
- Agarwal Sonali, Pandey GN, Tiwari MD. Data Mining in Education: Data Classification and Decision Tree Approach. International Journal of e-Education, e-Business, e-Management and e-Learning.2012 April; 2(2).
- Mahmood Ali Mohd, Qaseem Mohd. S, Rajamani Lakshmi, Govardhan A. Extracting Useful Rules Through Improved Decision Tree Induction Using Information Entropy. International Journal of Information Sciences and Techniques (IJIST). 2013 January; 3(1).
- Amarappa S, Sathyanarayana SV. Data classification using Support vector Machine (SVM), a simplified approach. International Journal of Electronics and Computer Science Engineering. ISSN-2277-1956.
- Tian Xia. Support Vector Machine Based Educational Resources Classification. International Journal of Information and Education Technology. 2016 November; 6(11).
- The Rapidminer website. Available from: http://rapidminer.com.
- The Mathworks website. Available from: http://www.mathworks.in.
- There are currently no refbacks.
This work is licensed under a Creative Commons Attribution 3.0 License.