How To Find The ROC In A Graph

By Trading Automation 03 September 2026

How To Find The ROC In A Graph can inspire different questions among people researching Trading. To simplify the search process, this Trading article provides relevant information. Read through the guide to build context.

To find and plot an on a graph, you plot the True Positive Rate (TPR) on the y-axis against the False Positive Rate (FPR) on the x-axis for every possible classification threshold of a model. 

Steps to Find and Plot an ROC Curve

• Gather predictions and actual classes: Collect your dataset's actual labels (0 or 1) alongside the predicted probability scores from your classification model. 
• Set classification thresholds: Sort the predicted probabilities from highest to lowest. Use these unique values as your decision thresholds. 
• Calculate TPR and FPR for each threshold:
  • Classify data points as positive or negative based on whether they meet or exceed the current threshold.
  • Count the True Positives (TP), False Positives (FP), True Negatives (TN), and False Negatives (FN).
  • Calculate TPR (Sensitivity) = $\frac{TP}{TP+FN}$
  • Calculate FPR (1 - Specificity) = $\frac{FP}{FP+TN}$ 
• Plot the points: Place each coordinate pair (FPR, TPR) onto a graph where the x-axis ranges from 0.0 to 1.0 (FPR) and the y-axis ranges from 0.0 to 1.0 (TPR). 
• Connect the dots: Draw lines connecting the sequential points from (0,0) to (1,1) to form the complete curve. A curve that bows heavily toward the top-left corner (0,1) indicates a high-performing model. 

Watch this video to learn how to plot an ROC curve using a step-by-step example: 

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#1. How to plot ROC Curve | Area Under Curve False Positive Rate vs True ...

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YouTube · Mahesh Huddar

How To Find The ROC In A Graph provides context for many common queries associated with Trading. Still, new questions can provide extra value. Keep the information as a reference and research new topics.