Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
Performance analysis of outcome based on learning is a system which will strive for excellence at different levels and diverse dimensions in the field of student’s interests. This system developed to analyze and predict the student’s performance only. The proposed framework analyzes the students’ demographic data, study related and psychological characteristics to extract all possible knowledge from students, teachers and parents. Seeking the highest possible accuracy in academic performance prediction using a set of powerful data mining techniques. The framework succeeds to highlight the student’s weak points. The realistic case study that has been conducted on 200 students proves the outstanding performance of the proposed framework in comparison with the existing ones.
Keywords:
Machine Learning (ML), Random Forest Algorithm.
Cite Article:
"STUDENTS PERFORMANCE PREDICTION USING RANDOM FOREST ALGORITHM", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.7, Issue 12, page no.444 - 449, December-2022, Available :http://www.ijrti.org/papers/IJRTI2212059.pdf
Downloads:
000205342
ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator