Student's Placement Prediction System

Computer Engineering

– Placement of students is one in every of the vital activities in academic establishments. Admission and name of establishments primarily depends on placements. Hence all institutions strive to strengthen placement department. The main objective of this paper is to analyze previous year’s student’s historical data and predict placement possibilities of current students and aids to increase the placement percentage of the institutions. We are not going to consider the placement of students not only by their academic performances but also aptitude, technical and communication skills, and segregating total student placement data into students placed in different streams to identify in which stream placements are more and use that data to predict the next year admission trends. Here we use different machine learning classification algorithms, namely KNearest Neighbors [KNN] algorithm, Random Forest. These algorithms independently predict the results and we then compare the efficiency of the algorithms, which is based on the dataset. This model helps the position cell at intervals a corporation to spot the potential students and concentrate to and improve their technical and social skills.

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