Student Placement Prediction System using Machine Learning

Abstract

Predicting the performance of a student is a great concern to the higher education managements. The purpose of training and placement management system is to automate the existing manual system by the help of computerized equipment’s, fulfilling their requirements, so that their valuable data/information can be stored for a longer period with easy accessing and manipulation of the same. 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. Managing placement and training records in any larger organization is quite difficult as the student number are high; in such condition differentiation and classification on different categories becomes tedious. Proposed system will classify the student data with ease and will be helpful to many educational organizations. There are lots of classification 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, Naive Bayes, KNN 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. For instance, here we will classify the student’s data set for placement and non-placement classes. Based on the result, higher education organizations can offer superior training to its students. Under this study information related to student’s performance measures is analysed in different perspectives to learn the achievements of the students through their activities