In the following table, we have 8 instances with 3 attributes Status, Suburb, and Shirt Size, and a Class Label. Each row is showing an instance.

	Status	Suburb	Shirt Size	Class
1	Married	Carlton	S	1
2	Married	Prahran	M	1
3	Married	Fitzroy	S	2
4	Single	St Kilda	M	2
5	Single	Glen Iris	L	3
6	Single	Coburg	L	3
7	Married	Ivanhoe	L	4
8	Married	Fitzroy	S	4

1. Calculate the information gain and gain ratio of 'Status' feature on the training dataset.(Note: you need to provide the results of each step to get full marks. You may need to use the following results: log2(1/2)=-1, log2(1/4)=-2, log2(1/8)=-3, log2(3/8)=-1.42, log2(5/8)=-0.68, log2(2/3)=-0.58, log2(1/3)=-1.58, log2(1/5)=-2.32, log2(2/5)= -1.32, log2 (3/5)=-0.74, log2(1)=0)

2. Does a decision tree exist, which can perfectly classify the given instances? If yes, draw that decision tree, otherwise, explain why not, by referring to the data.

3. If we use 'Status' to build a decision stump, what is the accuracy of the stump on the dataset?

4. If we use 'Suburb' to build a decision stump, what would you expect to see for the accuracy of the decision stump given an evaluation dataset that you have not seen before? Explain why the stump has good/bad accuracy.