TY  - JOUR
T1  - Adaptive Model for Campus Placement Prediction using Improved Decision Tree
AU - Sivakumar, Subitha AU - Selvaraj, Rajalakshmi 
JO  - Journal of Engineering and Applied Sciences
VL  - 12
IS  - 22
SP  - 6069
EP  - 6075
PY  - 2017
DA  - 2001/08/19
SN  - 1816-949x
DO  - jeasci.2017.6069.6075
UR  - https://makhillpublications.co/view-article.php?doi=jeasci.2017.6069.6075
KW  - Improved Decision Tree (IDT)
KW  -Educational Data Mining (EDM)
KW  -dataset
KW  -predicting
KW  -measures
KW  -achievements
AB  - Student’s academic achievements and their placement in campus selection becomes as challenging
issue in the educational system. Monitoring the student’s progress for their campus placement helps in
monitoring the student’s progression in the academic environment. Recently, educational data mining provides
a deep motivation to students for taking an effective decision as academic planners. This also helps the
educational institutions to have good intake of students based on student’s academic achievements and
appointments through the campus interview. In academic units, implementing this method will help in
evaluating and analyzing students and help the educators and institutions to make important decision that will
assist the students. This study demonstrates a novel method named “Improved Decision Tree (IDT)” for
segregating the eligible students for the campus selection based on the academic performance measures. This
model, based on the evaluated result obtained, it provides the suggestions in student’s placement predicting.
By using the proposed method, the relationship among student’s academic performance and their campus
placement is analyzed. Under this study information related to student’s performance measures is analyzed in
different perspectives to learn the achievements of the students through their activities.
ER  -