A Decision Tree Model to Predict Cervical Cancer Screening

Presenter(s): Seth Temple − Mathematics

Faculty Mentor(s): Stephen Fickas

Data Story

Research Area: Natural/Physical Science

I develop a decision tree model to predict if a female patient will be screened for cervical cancer. This project interests me because I want to apply machine learning to improve the health care system. I access the data from the website Kaggle. I use the pandas package to clean the data, and I wrangle some numerical columns with k-means clustering. Graphs will be produced by matplotlib. This project gives me practice in modeling with binary variables. As I plan to enter the actuarial field, this skill set is needed in building fraud and inspection models.