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Exercise

The strategy table and strategy curve

Repeating the calculations you did in the previous exercise for several acceptance rates, you can obtain a strategy table. This table can be a useful tool for banks, as they can give them a better insight to define an acceptance strategy.

You know how to compute a bad rate for a certain acceptance rate by now, so the function strategy_bank was written and loaded into your workspace to speed things up. This function computes the cut-off and bad rate for the acceptance rates that are multiples of 5% (0%, 5%, 10%, …).

Instructions

100 XP
  • Have a look at the function strategy_bank.
  • The vector predictions_cloglog contains predicted probabilities of default using the cloglog model you used in chapter 2, the vector predictions_loss_matrixcontains the predicted probabilities of default using the pruned tree including a loss matrix (previously constructed in chapter 3). Apply function strategy_bank to each of the prediction-vectors, assign the name strategy_cloglog and strategy_loss_matrix respectively.
  • The strategy tables can be obtained using the object names in combination with $table.
  • The strategy curves have been plotted for you. The strategy curve of the tree model shows pretty strange behavior. Because of the structure of classification trees, you might have a bigger chance for weird "jumps" here. Additionally, the tree with a loss matrix was a very big one, so this might be the result of overfitting!