Decision Tree Analysis
This project was created to give MIS students like me more practical data analysis experience while reinforcing the theories and procedures we learned from the Data Analytics class. In order to develop the prediction of the result variable for this project, I found a new relevant dataset online and used Decision Tree analysis.
Dataset URL: https://ww.kaggle.com/datasets/johnsmith88/heart-disease-dataset
Project PDF: Data Analytics Project
The four databases in this 1988 data set are Cleveland, Hungary, Switzerland, and Long Beach V. The “target” field references the patient’s having heart illness. 0 means there is no disease, while 1 means there is a disease.
With the completion of this project, I gained analytical skills such as choosing a dataset and describing the outcome variable and features for prediction. The relationship between the outcome variable and the features was explained, along with the insights that could be drawn from studying the data. The decision tree algorithm was used to find the best value for the minimum split for the dataset, and after creating the decision tree model, the nodes with the highest and lowest probabilities were identified. outlined the conclusions that can be drawn from looking at these nodes, as well as their connections to the attributes and outcome variable.