Every morning at 9:30am, the manager of a fast-food restaurant determines how many hamburgers to pre-make so they are ready to be immediately given to customers at lunchtime. If not enough are pre-made, customers will have to wait a long time in line, and might go to the competing fast-food restaurant next door instead. If too many are pre-made, some will spoil before they can be used.

d. Select a set of models from the list below, to create a solution that the manager can put together to determine how many hamburgers to pre[1]make each day

a.GIVEN daily data on sales, weather, holidays, day of week, and number of people who left because the line was too long, USE a clustering model TO estimate demand.

b. GIVEN daily data on sales, weather, holidays, day of week, and number of people who left because the line was too long, USE a random forest model TO estimate demand.

c. GIVEN past data on customers who leave based on time of day and line length, USE logistic regression TO estimate the probability of a customer leaving because the line is too long.

d. GIVEN past data on customers who leave based on time of day and line length, USE an optimization model TO estimate the probability of a customer leaving because the line is too long.

e. GIVEN an estimate of demand, the probability of a customer leaving because the line is too long, past arrival and service rates, cost of spoiled food, and estimated cost of lost customers, USE a support vector machine model TO find the number of hamburgers to pre-make that minimizes overall costs.