 |
A false positive error result in poor service to the customer if a call is incorrectly terminated, while. a false negative error can bring about significant financial loss to the company. With the cost-sensitive approach to the CART DT model, we assign costs associated with each outcome of True Positive (TP), True Negative (TN), False Positive (FP) and False Negative (FN) and then make predictions with the objective of minimizing total cost of outcomes, C̅, instead of minimizing error. Considering the cost of true predictions as zero, the cost of a FN error as 1, and for example, the cost of a FP error as one tenth the cost of a false negative (еч = 0.1), a cost-sensitive CART Decision Tree was developed using the same data as the previous accuracy-based model. This approach yielded a predictive accuracy of 84.5%. |
IEEE/ICACT20220012 Slide.12
[Big Slide]