ANTICIPATING PLACEMENT STATUS OF STUDENTS USING MACHINE LEARNING

Abstract

Every educational institute consider performance of students in terms of placements as an
indispensable factor towards its growth and brand building. Every aspiring student and their
parents also evaluate alternative institutes in terms of placement performance before getting
their ward admitted to a particular institute. Using records of students of past batches,
machine learning models can be derived and used for predicting placement status of future
batch students. This research study uses academic history, current academics, and socioeconomic background details of students to explore the applicability of machine learning in
this problem domain. Tree based methods is used to develop a predictive model and
understanding model behavior. The outcomes of this study are useful for students, faculty and
placement department of an educational institute in planning revisions in placement
preparation strategies.