Prediction of academic performance of students using machine learning

https://doi.org/10.53730/ijhs.v6nS1.7868

Authors

  • S. Preetha Associate professor, Department of Computer Science, Sri Ramakrishna College of Arts & Science for Women
  • D. Anitha Associate professor, Department of Computer Science, Sri Ramakrishna College of Arts & Science for Women

Keywords:

datamining, machine learning, logistic regression

Abstract

Data Mining is the process of analyzing data from different perspectives and summarizing it into useful information. It is the method of extracting patterns and drawing inferences from large and complex datasets. Data mining tools predict future trends and behaviors, allowing businesses to make proactive, knowledge-driven decisions. Educational Data Mining (EDM) refers to techniques, tools and research designed for automatically extracting meaning from large repositories of data generated by or related to people learning activities in educational system settings. One of the most important functions of EDM is to predict student performance based on past activity. This could include looking at past CGPA scores or internal assessments, student demography (income levels, school type etc.) or extracurricular activities.

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Published

25-05-2022

How to Cite

Preetha, S., & Anitha, D. (2022). Prediction of academic performance of students using machine learning. International Journal of Health Sciences, 6(S1), 11772–11779. https://doi.org/10.53730/ijhs.v6nS1.7868

Issue

Section

Peer Review Articles