Placement Prediction Analysis in University Using Improved Decision Tree Based Algorithm
||International Journal of Computer Trends and Technology (IJCTT)||
|© 2014 by IJCTT Journal|
|Year of Publication : 2014|
|Authors : Dammalapati Rama Krishna, Bode Prasad, Teki Satyanarayana Murthy|
|DOI : 10.14445/22312803/IJCTT-V17P136|
Dammalapati Rama Krishna, Bode Prasad, Teki Satyanarayana Murthy "Placement Prediction Analysis in University Using Improved Decision Tree Based Algorithm". International Journal of Computer Trends and Technology (IJCTT) V17(4):190-195, Nov 2014. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.
Data mining is an emerging research area applied where researchers applies for science and business application. In this paper data mining techniques are apply to placement prediction where recruitment taken place. Recruitment is one of the most important functions for any organization as they seek talented and qualified professionals to fill up their positions. Majority of the companies have been focusing on campus recruitment to fill up their positions. This method is the best way to get the right resources at the right time in the corporate world the young budding engineers. The focus of this paper is to identify whether the student will get placement or not. While the industry get the best talent from different institutes/universities, students too get chance to start their career with some of the best but it is very difficult in getting the placements. The result of this paper will assist will improve the performance of students in terms of placement. By applying the Improved Decision Tree Based classification algorithms on this data, we have predicted that students will placed in Recruitment Drives.
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Classification, Decision Tree, Data Mining, Educational Research, Placement, Predicting Performance, Decision tree