Measuring prediction performance using ROCR
A receiver operating characteristic (ROC) curve is a plot that illustrates the performance of a binary classifier system, and plots the true positive rate against the false positive rate for different cut points. We most commonly use this plot to calculate the area under curve (AUC) to measure the performance of a classification model. In this recipe, we will demonstrate how to illustrate an ROC curve and calculate the AUC to measure the performance of a classification model.
Getting ready
In this recipe, we will continue using the telecom churn dataset as our example dataset.
How to do it...
Perform the following steps to generate two different classification examples with different costs:
- First, you should ...
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