CIS8008 Assessment 3: Diabetes Data Analysis and Decision Tree

This report presents an analysis of a diabetes dataset using exploratory data analysis (EDA) techniques and decision tree modeling. The analysis was conducted using RapidMiner Studio, and involved identifying key variables for predicting diabetes risk. The report details the steps taken, including data import, summary statistics, correlation analysis, and chi-square tests to refine the variable selection. Furthermore, the report includes a review of the security and privacy policies of Automotive Holdings Group Limited (AHG), focusing on data governance principles and recommendations for improvement. The report also presents the decision tree model developed to predict diabetes based on the analyzed variables. The report contains tables, figures, and diagrams to support the analysis and conclusions.