Project
This project is based on Weka that can be downloaded at the website: https://www.cs.waikato.ac.nz/%7Eml/weka/downloading.html
Here, you will use WEKA's J48 decision tree algorithm to perform a data mining session with the cardiology patient data. Open the WEKA explorer and load the cardiology-weka.arff file (attached with the project). This is the mixed form of the dataset containing both categorical and numeric data. Recall that the data contains 303 instances representing patients who have a heart condition (sick) as well as those who do not.
Preprocessing Questions:
1. How many of the instances are classified as Healthy?
2. What percent of the data is female?
3. What is the most commonly occurring domain value for the attribute slope?
4. What is the mean age within the dataset?
5. How many instances have the value 2 for # of Colored Vessels?
Classification Questions using J48:
Perform a supervised mining session using 10 fold cross validation with J48 and class as the output attribute. Answer the following based on your results:
a. What attribute did J48 choose as the top-level decision tree node?
b. Draw a diagram showing the attributes and values for the first two levels of the J48 created decision tree.
c. What percent of the instances where correctly classified?
d. How many healthy class instances were correctly classified?
e. How many sick class instances were falsely classified as healthy individuals?
f. Determine how True Positive Rate (TP Rate) and False Positive Rate (FP Rate) are computed.