Diabetes Likelihood ML Model
A collection of machine learning methods used to predict diabetes.
Fall 2024
About the Project
The purpose of this project was to demonstrate my machine learning skills. The code was created in a Python Notebook using the numpy, pandas, matplotlib, seaborn, and sklearn libraries. I used a Random Forest Classifier along with PCA for dimension reduction. I also analyzed results using confusion matrices and by plotting decision boundaries
GitHub Repository: github.com/holdencasey7/diabetes-likelihood
Visual Results: Diabetes Model Results PDF
87% Accuracy
18% False Negative Rate
9% False Positive Rate
