For this project, I was required to find a csv dataset online that had not been used in class before, run a decision tree analysis on the dataset, and answer questions related to the decision tree. I found a dataset on Kaggle that had data on patient glucose level, blood pressure, age, genetic predisposition for diabetes, and other predictors, as well as a 0 or 1 value to show that the patient was diabetic. Using this data, I made a decision tree that showed the probability of a patient being diabetic based on the predictors. After I was done making the decision tree, I answered various questions such as the best minimum split value, which had the highest/lowest probability, and to list some datapoints and their probabilities. This was a solo project, all the work was done myself. I gained a deeper insight into how decision trees work, and I feel more confident in using datasets to make predictions.
