The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Wise Apply on a Machine Learning-Based College Recommendation Data System
|
|
Author(s): Jyoti P. Kanjalkar (Vishwakarma Institute of Technology, India), Gaurav N. Patil (Vishwakarma Institute of Technology, India), Gaurav R. Patil (Vishwakarma Institute of Technology, India), Yash Parande (Vishwakarma Institute of Technology, India), Bhavesh Dilip Patil (Vishwakarma Institute of Technology, India)and Pramod Kanjalkar (Vishwakarma Institute of Technology, India)
Copyright: 2024
Pages: 12
Source title:
Data-Driven Intelligent Business Sustainability
Source Author(s)/Editor(s): Sonia Singh (Toss Global Management, UAE), S. Suman Rajest (Dhaanish Ahmed College of Engineering, India), Slim Hadoussa (Brest Business School, France), Ahmed J. Obaid (University of Kufa, Iraq)and R. Regin (SRM Institute of Science and Technology, India)
DOI: 10.4018/979-8-3693-0049-7.ch018
Purchase
|
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.
Related Content
|
D. Lavanya, Divya Marupaka, Sandeep Rangineni, Shashank Agarwal, Latha Thammareddi, T. Shynu.
© 2024.
17 pages.
|
|
A. Sabarirajan, N. Arunfred, V. Bini Marin, Shouvik Sanyal, Rameshwaran Byloppilly, R. Regin.
© 2024.
14 pages.
|
|
P.S. Venkateswaran, M. Lishmah Dominic, Shashank Agarwal, Himani Oberai, Ila Anand, S. Suman Rajest.
© 2024.
16 pages.
|
|
Thangaraja Arumugam, R. Arun, R. Anitha, P. L. Swerna, R. Aruna, Vimala Kadiresan.
© 2024.
12 pages.
|
|
Thangaraja Arumugam, R. Arun, Sundarapandiyan Natarajan, Kiran Kumar Thoti, P. Shanthi, Uday Kiran Kommuri.
© 2024.
15 pages.
|
|
H. Hajra, G. Jayalakshmi.
© 2024.
17 pages.
|
|
H. Hajra, G. Jayalakshmi.
© 2024.
19 pages.
|
|
|