Explore –Journal of Research
Peer Reviewed Journal
ISSN 2278–0297 (Print)
ISSN 2278–6414 (Online)
Vol. XIV No. 2, 2022
© Patna Women’s College, Patna, India
Reducing college dropout ratio using Machine Learning
• Rakesh Kumar • Anshuman
Received : April 2022
Accepted : May 2022
Corresponding Author : Rakesh Kumar
Abstract : Machine Learning (ML) has proved significant in almost all walks of life. The presented work focuses on the implementation of ML algorithms in the field of humanity and education. Every year a large number of students choose to drop their studies before completing college. Some of them build their own future as entrepreneurs and some struggle throughout their lives to meet the ends. In both cases, the institute or some deserving candidates suffer. This is becoming a serious concern, as all over
the world the dropout rates are significantly high. This work focuses on the notion of implementation of Machine Learning algorithms to classify the traits of various students based on their activities and past performances to describe the dropout ratio and also certain measures to reduce the numbers.the world the dropout rates are significantly high. This work focuses on the notion of implementation of Machine Learning algorithms to classify the traits of various students based on their activities and past performances to describe the dropout ratio and also certain measures to reduce the numbers.
Keywords : Machine Learning, Artificial Intelligence, Supervised Learning, Classification, Clustering.
Rakesh Kumar
Faculty – Computer Applications,
LNMI, Patna
Email-id: rakeshkr1@lnmipat.ac.in
Anshuman
Assistant Professor,
Amity University Patna
Email-id: aaryaa@ptn.amity.edu
