Valley TV sells TV sets. It does not sell smart TVs so customers do not come to Valley TV if they want to purchase smart TVs$.$

$q,$

$q,$

Lonstruct a conrusion matrix tor the curom point

u$.$su$.$

$\backslash$table$[[,$Confusion Matrix $(0\mathrm{.}30)],[$Predicted Outcomes,Total$],[$Buyers$,$Non$-$Buyers$],[\backslash$table$[[$Actual$],[$Outcomes$]],$Buyers,$162,18,180],[$Non$-$Buyers,$513,207,720],[$Total$,675,225,-900]]$

the $$45$ it spends on that customer. Construct the payoff matrix and determine which cut off value Valley TV should use.

Start by constructing the payroll matrix. $($Complete all answer boxes. Enter a $0$ for any zero balances. Enter a spend or loss amount with a minus sign or parentheses.$)$

Payoff Matrix

$\backslash$table$[[,$Predicted Outcomes$],[,$Buyers,Non$-$Buyers$],[\backslash$table$[[$Actual$],[$Outcomes$]],$Buyers,,$],[$Non$-$Buyers,,$]]$

Calculate the payoff at each cutoff probability.

T$$tal payoff at cutoff $0\mathrm{.}70=$

Total payoff at cutoff $0\mathrm{.}30=$

Which cut off value should Valley TV use?

Valley TV should use the cutoff value at $$ because it results in the $$ predicted payoff.

Requirement $3.$ Are there any other factors Valley TV should consider before building such a model?

A$.$ Valley TV should consider the potential side effects of marketing too aggressively. If the company's marketing efforts irritate or offend interested customers, they may turn those customers away and lose sales.

B$.$ Valley TV should consider whether or not they could make their ROC curve less predictive.

$q,$ C$.$ Valley TV should consider whether they could increase the Gini impurity of the data set used to make the prediction models.

$q,$ D$.$ No other factors need to be considered beyond those already analyzed when producing the prediction models discussed above.