Student's Placement Prediction Using Support Vector Machine
DOI:
https://doi.org/10.32628/CSEIT206511Keywords:
Machine learning, SVM, Placement Prediction, KNN, Data Analysis.Abstract
The ultimate goal of any educational institution is offering the best education experience and good placement opportunity to the students. Identifying the students who need extra support and taking the appropriate actions to enhance their performance plays an important role in achieving good placement. Student’s academic achievements and their placement in campus selection becomes as challenging issue in the educational system. Proposed student prediction system is most vital approach which may be used to differentiate the student data/information on the basis of the student performance. The proposed system will classify the student data with ease and will be helpful to many educational organizations. There are lots of machine learning algorithms and statistical base technique which may be taken as good assets for classify the student data set in the education field. In this paper, various machine learning algorithms like Naïve Baiyes, SVM, KNN, decision tree algorithm has been applied to predict student performance which will help to identify performance of the students and also provides an opportunity to improve to performance.
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