Q4) [18 points] Explain different stages in customer life cycle, the business process organized around the customer life cycle, and mention how data mining can help in each process. Q5) [6 points] Explain 3 different ways you would suggest to deal with missing values in a dataset? Mention the pros and cons of each approach. Q6) [6 points] In the data pre-processing stage, we might observe almost-unary columns (i.e. columns with almost only one value). (a) How might this column be generated? Give two examples. (b) Does this type of variable have significant value in data mining? How would you treat almost-unary columns in your data?