Andrew Wirz
Gianmarco Huaytan
Mounish Kandumalla
Vinh Tang
Austin Sanders
Prediction model for assessing student success using the K-Nearest-Neighbor algorithm. The model will take in a plethora of answers provided by the prediction form. These answers will be broken up and passed into each prediction model that correspond with those retrieved features. Once each model is ran, the weighted grade predictions are summed up to provide the final academic performance prediction. From this, we can determine if an individual is expected to have poor academic performance based on the external factors that are not explicitely associated such as household income, alcohol consumption, etc..
Final To-Do:
- Create Final model for data set
- Create input form for testing full model
- Write up report (Can do most before code is done)
- Create presentation
- Record presentation
- ???
- Profit 🤑