This is a CS related topic, if you think this is not related to CS, then you are not a computer scientist!!

4. Suppose we have used a decision tree algorithm to build a classifi- cation tree model for detection of Fault-Prone (FP) and Not Fault- Prone (NFP) program modules or objects. We have encoded FP=1 and NFP=0. Also, assume that we are interested in a particular leaf node (NODE t) in the tree model with mean value of 0.25. We would like to classify an object from the test data set which falls in this leaf node (NODE t). Predict this object as FP or NFP for the following cases. (a) 5 (or c) = 0.30 (b) 5 (or c) = 2.5 Show all your work! 4. Suppose we have used a decision tree algorithm to build a classifi- cation tree model for detection of Fault-Prone (FP) and Not Fault- Prone (NFP) program modules or objects. We have encoded FP=1 and NFP=0. Also, assume that we are interested in a particular leaf node (NODE t) in the tree model with mean value of 0.25. We would like to classify an object from the test data set which falls in this leaf node (NODE t). Predict this object as FP or NFP for the following cases. (a) 5 (or c) = 0.30 (b) 5 (or c) = 2.5 Show all your work