Predicting student placements using Bayesian classification

Rapidly increasing educational institutions, are imposing a great demand of quality education and placements for the benefit of the students as well as of the Institutions. In this paper application of Bayesian theorem on educational dataset has been proposed to predict placement results. Results are evaluated using Naive Bayes Classifier in WEKA and RapidMiner tool. Results generated will help instructors, educators as well as students to focus on those aspects which help in improving student placements.