Open Access Journal

ISSN : 2394-2320 (Online)

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

Open Access Journal

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

ISSN : 2394-2320 (Online)

Student’s Performance Analysis using Random Forest and Prediction using Light GBM

Author : Dr.K.Madhavi 1 Mogulla Pallavi 2 Rumana Tarannum 3 Sirikonda Manasa 4 Kurremula Sreenija.. 5

Date of Publication :28th June 2023

Abstract: In the area of the student's interests, the student's performance analysis system, which is focused on learning, aspires to excellence on many different levels and dimensions. This method is designed to evaluate and forecast student performance. The suggested approach examines student demographics, academic data, parental education, and other factors in an effort to elicit as much data as possible from students, teachers, and parents. Analyzing student academic performance is essential for academic institutions and instructors in order to explore methods to improve individual student performance. Using a set of data mining algorithms to achieve the maximum possible accuracy in student performance prediction. This framework is effective in highlighting the student's weaknesses which are based on experimented studies for improving student’s academic achievement.

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