Senior IS Thesis Software

Written by Minhwa Lee

(Update: 10/07/2020 - Currently Working) (Note: The BRFSS dataset is too large to upload here :( )

Purpose

• This is a year-long Independent Study (I.S.) project: undergraduate research program required for all seniors from The College of Wooster consisting of thesis submission, oral dissertation, and paper presentation at the college's annual I.S. symposium planned on April 2021

(Here's the link for details of I.S.: https://www.wooster.edu/academics/research/is/)

• A joint research about what factors including demography, economic status, and health-related accessibility affect an US adults' probabilities of having a depressive disorder, as well as of predicting patients with a depressive disorder, through a combination of statistical learning methods and machine learning techniques using Python Scikit-learn and R

• The dataset: BRFSS (Behaviroal Risk Factor Surveillance System) released from CDC of the United States in 2018

• Investigate the following three learning methods - logistic regression, decision trees, and support vector machine - to conduct pattern classification of patients from the US who are suffering from a depressive disorder in 2018

Software

dt_data.py

A Python program to conduct decision tree learning for the BRFSS data set (target dataset)

dt_tennis.py

A Python program to do decision tree learning for an example data set (tennis)