Data mining problems; For each of the following problem scenarios, decide if a solution would best be addressed with supervised learninig, unsupervised clustering, or database query. If you decide that supervised learning or unsupervised clustering is the best answer, list several input attributes you believe to be relevant for solving the problem. 1. what characteristics differentiate people who have had back surgery and have returned to work from those who have had back surgery and have not returned to their jobs? 2. When customers visit my Web Site, What products are they most likely to buy together? 3. what percent of my employees miss one or more days of work per month? 4. what relationships can I find between an individuals's height, weight, age and favorite spectator sport? 5. A list of all credit card holders who used their credit card to purchase more thatn RM300 in groceries during the month of October. 6. Develop a general profile for credit card customers who take advantage of promotions offered with their credit card billing. 7. differentiate individuals who are poor credit risks from those who are likely to make their loan payments on time. 8. forcast which telephone subscribers are likely to change providers during the next three months. 9. Estimate the grade-point average (GPA) of a graduate student based on that student's undergraduate GPA. 10. predicting the price of a stock three months into the future 11. identifying whether or not certain financial or personal behavior indicates a possible terrorist threat 12. finding out which items in a supermarket are purchased together and which items are never pruchased together. 13. Target marketing of a niche product for small-capitalization business that does not have a large marketing budget. 14. Determine how telecommunication services can be packaged together to maximize revenur. 15. identify customers who would likely want other services like such as money market accounts, investment services and car loans