 # How do you create a ROC curve in Excel?

The ROC curve can then be created by highlighting the range F7:G17 and selecting Insert > Charts|Scatter and adding the chart and axes titles (as described in Excel Charts). The result is shown on the right side of Figure 1. The actual ROC curve is a step function with the points shown in the figure.

Find out everything you need to know about it here. Also, how does a ROC curve work?

A ROC curve is constructed by plotting the true positive rate (TPR) against the false positive rate (FPR). Similarly, the false positive rate is the proportion of observations that are incorrectly predicted to be positive out of all negative observations (FP/(TN + FP)).

Also Know, what does ROC curve tell you? The ROC curve In a Receiver Operating Characteristic (ROC) curve the true positive rate (Sensitivity) is plotted in function of the false positive rate (100-Specificity) for different cut-off points. Each point on the ROC curve represents a sensitivity/specificity pair corresponding to a particular decision threshold.

Also know, what is the threshold in ROC curve?

A really easy way to pick a threshold is to take the median predicted values of the positive cases for a test set. This becomes your threshold. The threshold comes relatively close to the same threshold you would get by using the roc curve where true positive rate(tpr) and 1 - false positive rate(fpr) overlap.

How is ROC score calculated?

The false positive rate is calculated as the number of false positives divided by the sum of the number of false positives and the number of true negatives. It is also called the false alarm rate as it summarizes how often a positive class is predicted when the actual outcome is negative.