The Project consists of three folders: Code, Figures and HelperFiles. The Code folder consists of all the files required to run the program. The Figures folder consists of a list of images depicting the results and trends obtained. The HelperFiles folder consists of a list of files which are read by the programs to perform computation. These files provide a list of the features chosen, the list of prediction variables and the map of the variables with their type : Categorical or Continuous.
How to run the project:
- The project can be executed by running the run_me.py file.
- The dataset can be downloaded from https://collegescorecard.ed.gov/data/documentation/
- The zip file needs to be extracted inside the MLProject folder along with the Code, Figures and HelperFiles directories.
- The path to the file needs to be changed in the run_me.py file.
- The run_me file first calls the functions from the preprocessing.py file to perform preprocessing.
- The next step is to perform imputations on the missing data. The functions related to imputations are present in the imputations.py file.
- We then run the regression.py file which contains methods to transform the data, perform dimensionality reduction and initalize a regressor.
- The regression_pipeline.py file consists of methods to perform cross validation , choose the best hyperparameter and compute the RMSE scores. The utils file consists of miscellaneous utility methods.
- Python : 2.7
- Sklearn: 0.18
Mean Earnings:
Mean Debt:
