Machine Learning-Based College Admission Predictor: A Telegram Bot for Indian Engineering Colleges
DOI:
https://doi.org/10.15157/QR.2024.2.1.1-6Keywords:
Machine learning algorithms, Chatbot, Random Forest, Prediction, Linear RegressionAbstract
This study addresses the challenge of accurately predicting college admissions in India, where students often struggle to identify suitable colleges based on their entrance exam scores. The research explores the development of a College Predictor Bot that leverages key factors, specifically JEE and CET scores, to estimate the likelihood of admission to various Indian colleges. The model is trained on historical admissions data from multiple institutions, encompassing a wide range of student profiles and performance levels. Methodologically, the study employs machine learning algorithms, including random forest and decision tree models, to analyze the entrance exam scores and generate predictions. The model’s accuracy is evaluated through rigorous statistical analysis, with significant correlations observed between entrance exam scores and admission outcomes. The findings indicate that the College Predictor Bot can effectively predict admissions, providing students with valuable insights into their college options. The broader implications suggest that this tool could simplify the college selection process, offering a more transparent and informed approach to admissions in the Indian education system.
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This work is licensed under a Creative Commons Attribution 4.0 International License.