How Do You Find The ROC

By Trading Automation 02 September 2026

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To calculate a Receiver Operating Characteristic (ROC) curve, you plot the against the False Positive Rate (FPR) across various classification thresholds. 

Steps to Calculate an ROC Curve

• Collect predictions: Gather your model's predicted probabilities and the true binary labels (0 or 1) for each data point. 
• Set thresholds: Sort the predicted probabilities from highest to lowest to use as potential classification cutoffs. 
• Calculate rates for each threshold: For every threshold value, convert probabilities into class predictions (above threshold = positive, below = negative) and compute two metrics:
  • True Positive Rate (TPR) / Sensitivity:
  • False Positive Rate (FPR) / (1 - Specificity):  
• Plot the graph: Put the FPR on the x-axis and the TPR on the y-axis, then connect the coordinate points to form the curve. 
• Calculate AUC (Optional): Compute the Area Under the Curve (AUC) by measuring the total area beneath the ROC line to get a single performance score from 0.5 (random chance) to 1.0 (perfect model). 

Learn more about how to construct an ROC curve and compute its metrics by watching this video: 

10:17

The ROC Curve (Receiver-Operating Characteristic Curve) — Topic 84 of ...

4,3K views · 4 years ago

YouTube · Jon Krohn

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