A REVIEW ON DATA MINING AND MACHINE LEARNING METHODS FOR STUDENT SCHOLARSHIP PREDICTION

Authors

  • Khutaija Abid Assistant Professor, Department of IT, Lords Institute of Engineering and Technology, Hyderabad Author
  • Mohd Shoaib, Omer Mohammed, Mohammed Raziuddin Faisa B.E. Student, Department of IT, Lords Institute of Engineering and Technology, Hyderabad Author

Abstract

This review paper examines the application of Machine Learning and Data Mining techniques for
predicting student scholarships. It conducts a comprehensive literature survey on the methodologies used in this
area, emphasizing the significance of datasets in achieving accurate predictions. Machine Learning has gained
considerable traction across various industries, including IT, education, and business sectors. The study discusses
several ML/DM algorithms such as Naïve Bayes, Decision Tree, and k-NN, highlighting their effectiveness in
determining scholarship eligibility. The proposed model aims to generate a list of deserving scholarship candidates,
accompanied by a detailed analysis of the accuracy achieved by each technique employed in this study.

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Published

2024-09-20

Issue

Vol. 14 No. 7 (2024): September

Section

Articles

How to Cite

A REVIEW ON DATA MINING AND MACHINE LEARNING METHODS FOR STUDENT SCHOLARSHIP PREDICTION. (2024). INTERNATIONAL JOURNAL OF MANAGEMENT RESEARCH AND REVIEW, 14(7), 46-55. https://ijmrr.com/index.php/ijmrr/article/view/271

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