A Data Mining Solution to Predict Campus Placement

The Campus placement is one of the most important objectives for students as well as for educational institutes. The main goal of every student is to get placement in a well-known desired companies. In most of the institute, admission depends on the placement factor which they provide to their under graduate. This paper emphasizes whether a student will get placed or not at the primitive stage, which will give us an advantage and persuade us to take further action for that student to get placed. This will indirectly decrease the workload of the training and placement cell. Our experiment revolve around the forecasting of the under graduate getting placed in the certain companies. We have done suitable data pre-processing for the removal of all the redundant features. Machine Learning models like Logistic regression, SVM classification, Decision Tree classifier, Gaussian Naïve Bayes, Random Forest Classifier, k-NN classification, and Ensemble Voting classifier have been used in this paper and it has been found that the Voting classifier achieved the highest accuracy and outperform.