Grade Prediction of Educational Institute Using ML Algorithm

Abstract

A massive amount of data is reproduced across numerous pursuits such as education, medical science, defenses, social media, and so on and so forth. Machine Learning (ML) and Data Mining (DM) are techniques that can be used to identify and improve the hidden patterns automatically through experience seen as a subset of Artificial intelligence. One of the key areas of this application is Educational Data Mining(EDM) which uses ML and statistics to extract large repositories of data associated with learning activities. These learning management systems are majorly used to predict college grades. The proposed model is built to predict the future grade of colleges and universities, established on the current activities they execute. Machine learning algorithms are found to be very practical and effective. It is the most valuable under circumstances where the individual doesn’t have an adequate amount of knowledge. ML algorithm predicts the future based on the input given to it, it investigates and analyzes given input data. They are trained based on it and infer a hypothesis /theory. The proposed model has used the Random Forest regression (RFR) algorithm which will help colleges to priorly know the grades and if these grades are less than what they anticipated they can improve them by enriching the current activities.