COMP4801 Final Year Project Mining HKUCS Graduate Student Data: Extraction, Analysis, and Prediction Final Report

نویسندگان

  • Reynold Cheng
  • Jiafeng Hu
چکیده

Educational Data Mining (EDM) is an emerging field that uses statistical and machine learning algorithms to find patterns in massive educational data sets. It is commonly used to solve problems such as predicting admission outcome and student performance. This project applies educational data mining techniques to the admission data of the graduate programs in the Computer Science Department of the University of Hong Kong (HKUCS). The objective of the project is to build a web application with a user-friendly interface that visualizes and analyses admission data using the following algorithms: Decision Tree algorithm, Association Rule algorithm and Logistic Regression algorithm. Based on the admission patterns that are found, the web application suggests a ranked list of candidates for admission decisions.

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تاریخ انتشار 2017