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 College-Scorecard 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.

Tools and Technologies used:
Python : 2.7
Sklearn: 0.18