ML_Project

CIS4930: Introduction to Machine Learning Final Project - Analysis in characteristics for diabetes detection

Group Members:

• David Visbal Gomez
• Joshua Delamater
• Jesus Lopez
• Christian Rodriguez
• Vance Boudreau

Dataset:

We will use a dataset sourced from Kaggle for diabetes prediction. The dataset features 9 columns, including:

• Gender
• Age
• Hypertension status
• Heart disease status
• Smoking history
• Body Mass Index (BMI)
• Hemoglobin A1c levels
• Blood glucose levels
• Diabetes status

The dataset contains integer, decimal, and string data types. It is essential for our project as it provides critical information for determining diabetes.

Initial Plan:

1. We plan to find the underlying factors that have a heavy correlation to diabetes.
2. We plan to use a combination of a linear regression model for the numerical data and a classification tree for the string data.
3. We will distribute the workload among the members of the group, and we will clean the data and scale the data so that the model can converge quicker.