Tutorials

The Receiver Operating Characteristic (ROC) curve is a graphical representation of a classifier's performance across different thresholds, showing the trade-off between the True Positive Rate (TPR) (or Sensitivity) and the False Positive Rate (FPR). Manipulating or interpreting the ROC curve often involves understanding how to adjust thresholds and metrics.

Here’s how you can manipulate or tweak aspects of the ROC curve:

1. Adjusting the Decision Threshold

• The decision threshold determines whether a classifier's output is classified as positive or negative.
• By changing the threshold:
• Lower threshold: Increases sensitivity (TPR) but also increases FPR.
• Higher threshold: Decreases FPR but may reduce TPR.