The purpose of this project is to build decision trees to make decision if a patient has heart disease or not. Instructions: 1. Data Exploration: Summarize the numerical data using frequency distribution, cross tabulation, descriptive measures and/or other appropriate technique you think which are appropriate to study this data set, examine correlations, and so on. Please note that, besides studying all attributes for all samples/rows, you may also need to study/summarize data based on two diagnosis: heart disease or no heart disease. 2. Create Dashboards. 3. Build decision tree. Make sure that before you build decision tree, divide this data set into training set (e.g. 70-80% of the data) and test set (e.g. 20% - 30% of the data). 4. Based on model built, classify test data and compare your predication/classification results with the actual diagnosis. Calculate the rate of the accuracy. 5. In your workbook, create a Report Sheet, write up your findings as a formal report in this Report Sheet. Make sure that your formatting is clear and easy to read