Timothy Burt, Melie Lewis, Koby Pascual, Yutian Tang
Python/R-based program with GUI that uses data mining techniques (clustering/classification) to predict success/failure trends of students based on course choices along with retention information. Goals: * Identify common course taking patterns for first-time, full-time freshmen. * Predict student retention based on the identified course clusters and pre-existing risk factors. * Tools that can be used by academic advisors to better aid in enrollment decisions.
Presentation + demonstration video: https://www.youtube.com/watch?v=VxCeQhM9xIc Demo only video: https://www.youtube.com/watch?v=0EEFfizu4D0
To run the GUI program, run 'python Main.py' from inside the GUI directory.
No setup needed. If you receive module errors, you may need to install those modules. An easy way is with '(sudo) pip install [module]'
| [HUANG97] | Huang, Z.: Clustering large data sets with mixed numeric and categorical values, Proceedings of the First Pacific Asia Knowledge Discovery and Data Mining Conference, Singapore, pp. 21-34, 1997. |