Open AccessAcademic Performance Prediction of Undergraduate Students using Decision Tree Algorithm
Author(s) -
Rashmi V. Varade,
Blessy Thankanchan
Publication year - 2021
Publication title -
samriddhi - a journal of physical sciences, engineering and technology
Language(s) - English
Resource type - Journals
eISSN - 2454-5767
pISSN - 2229-7111
DOI - 10.18090/samriddhi.v13is1.22
Subject(s) - decision tree , variety (cybernetics) , field (mathematics) , computer science , decision tree learning , data mining , data science , tree (set theory) , machine learning , artificial intelligence , mathematics , mathematical analysis , pure mathematics
Data mining is a technique for extracting meaningful information or patterns from large amounts of data. These techniques are frequently utilised for analysis and prediction in practically all fields around the world. It's employed in a variety of fields, including education, business, health care, fraud detection, financial banking, and manufacturing engineering. This study explores the Decision Tree data mining methodology for predicting undergraduate students' academic performance.