If вЂњSettledвЂќ means good and вЂњPast DueвЂќ is understood to be negative, then using the design of this confusion matrix plotted in Figure 6, the four areas are divided as True Positive (TN), False Positive (FP), False bad (FN) and real Negative (TN). Aligned with all the confusion matrices plotted in Figure 5, TP may be the good loans hit, and FP could be the defaults missed. We have been keen on those two areas. To normalize the values, two widely used mathematical terms are defined: true rate that is positiveTPR) and False Positive Rate (FPR). Their equations are shown below:
In this application, TPR could be the hit price of great loans, plus it represents the ability of creating funds from loan interest; FPR is the lacking rate of standard, and it also represents the likelihood of losing profits.
Receiver Operational Characteristic (ROC) bend is considered the most widely used plot to visualize the performance of the category model after all thresholds. In Figure 7 left, the ROC Curve associated with Random Forest model is plotted. This plot basically shows the partnership between TPR and FPR, where one always goes into the direction that is same one other, from 0 to at least one. an excellent category model would will have the ROC curve above the red standard, sitting because of the вЂњrandom classifierвЂќ.