Logistic Regression

This project implements a logistic regression model from scratch. You can easily run the analysis on the dataset by following the instructions below.

Contributors

Created by Marc-Antoine Nadeau, Jessie Kurtz, and Baicheng Peng

How to Run

To perform logistic regression on the Diabetes Health Indicators dataset:

1. Navigate to the DiabetesHealthIndicators folder.
2. Run the PrepareAndTestDataset.py file.

Dataset

• DiabetesHealthIndicators/Data: Contains the data for logistic regression.

Results

Any resulting figures/graphs will be saved in their respective folders:

• DiabetesHealthIndicators/Results: Contains the results for logistic regression.

Helper Functions

The Helper.py and PlotHelpers.py file contains all the helper functions used throughout this project.

Prerequisites

Make sure you have the following Python libraries installed:

• numpy
• pandas
• matplotlib
• seaborn
• scikit-learn

You can install them using pip:

pip install numpy pandas matplotlib seaborn scikit-learn