Student Placement Prediction Using Supervised Machine Learning
M. Siva Surya, Sathish Kumar, D. Gandhimathi
Abstract
Student placement is one of the most significant activities at academic institutions. Placements have a large role in determining admission and the name of the university. As a result, each university attempts to strengthen its placement services. The goal of this study is to analyse recent year's pupil data and utilise it to predict current pupil's placement chances. This model incorporates a prediction algorithm. Any assistance in this area will increase an university's capacity to place pupils. In the long term, this will benefit both students and the university. An method for predicting is included in this model. The study's data was acquired from the very same institution that would do the placement prediction, and it was preprocessed appropriately. In terms of accuracy, this proposed models were tested to other classic classification algorithms. According to the results, the proposed technique surpasses the other algorithms by a massive margin.