A Novel Machine Learning Recommender System for Generating College Recommendations

College/University Admission Assistant

Abstract

This paper introduces Usher-AI, a Machine Learning recommender system utilizing the K-Nearest Neighbors (KNN) algorithm, designed to forecast university acceptance for prospective students and generate college recommendations. By analyzing historical student and university data of accepted and denied applicants, this method aims to assist individuals in estimating their chances of college acceptance, thereby enhancing their decision-making process. This paper details the steps in the method’s development and implementation, including the data preprocessing, model training, and evaluation. The predictions generated by Usher-AI including, chances of acceptance using student fit and profile, demonstrate promising accuracy in predicting college acceptance, providing valuable insights for both applicants and university admissions. In addition, the Usher-AI-generated college recommendations inform student decisions in selecting colleges during the application cycle.