Please use this identifier to cite or link to this item: https://gnanaganga.inflibnet.ac.in:8443/jspui/handle/123456789/16751
Title: Student'S Performance Prediction Using Machine Learning Algorithms- a Comparative Study
Authors: Kadu, Varun
Mishra, Pawan Kumar
Dandhare, Sarthak
Patni, Jagdish Chandra
Chandel, Palash
Pathak, Soham
Bahadure, Nilesh
Keywords: Decision Tree
Decision Tree Method
Entropy
K-Nearest Neighbour
Knn
Regression Model
Support Vector Machine
Tree Classifier
Issue Date: 2024
Publisher: 2024 OPJU International Technology Conference on Smart Computing for Innovation and Advancement in Industry 4.0, OTCON 2024
Institute of Electrical and Electronics Engineers Inc.
Abstract: Predicting and enhancing student performance has been a crucial topic of concentration in education amid the quick development of technology and the increasing need for higher-quality instruction. The use of machine learning technology to forecast pupils' academic success is covered in detail in this study report. This research project examined several prediction models that reliably predict students' performance according to a range of extracurricular and academic attributes. An overview of machine learning methods is given in this paper to automate the process of predicting students' academic performance and extracting outcomes. © 2024 IEEE.
URI: https://doi.org/10.1109/OTCON60325.2024.10687450
https://gnanaganga.inflibnet.ac.in:8443/jspui/handle/123456789/16751
ISBN: 9798350373783
Appears in Collections:Conference Papers

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