Cost-Based Thresholds: A Cost Matrix, Expected Cost per Run & the Cheapest Cut-Off
This lesson is part of the course
In this lesson
You price every cell of the confusion matrix, compute the expected cost per run for ten thresholds, pick the cheapest one with MIN and INDEX/MATCH and compare it with the break-even formula.
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Lessons in this course
- The Accuracy Trap: 3 Faults in 100 Runs, Confusion Counts & the «Always OK» ModelFree
- Metrics That Respect the Minority: Balanced Accuracy, the Matthews Coefficient, F1 & Fβ Locked
- Random Undersampling & Oversampling: Given Draw Tables, New Class Shares & What Gets Lost Locked
- Synthetic Minority Samples: Neighbour Distances, the k Nearest & New Points by Interpolation Locked
- Class Weights: n ÷ (k × n_class), a Weighted Log-Loss & a New Best Cut-Off Locked
- Cost-Based Thresholds: A Cost Matrix, Expected Cost per Run & the Cheapest Cut-Off Locked
- Probability Correction After Resampling: Training vs Real Prevalence & a Calibration Table Locked
- Capstone – Comparing Strategies: Balanced Accuracy, MCC, Recall, Expected Cost & a Ranked Summary Locked