Wise Apply on a Machine Learning-Based College Recommendation Data System

Abstract

This chapter presents a college recommendation system using machine learning with the features of branch, caste, location, and fees. The system aims to provide personalized recommendations to students based on their preferences and past academic performance. The dataset used in the study consists of information about various colleges, including their location, fees, available branches, and the percentage of students belonging to different castes. The system uses a combination of machine learning algorithms, including decision trees and random forests, to provide accurate and efficient recommendations. The Adaboost algorithm is used to find colleges with similar features to the student's preferences, while decision trees and random forests are used to make predictions based on past data. The proposed system is evaluated using metrics such as accuracy, precision, recall, and F1 score. The results show that the system provides highly accurate and personalized recommendations to students.