Model Validation

Backtest Results

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Historical validation — how did the models perform in the past?

Summary Metrics
Total Backtest Years
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1990 to present · 4 bands
Average ROC-AUC
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Average across 4 bands
Best Band
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Highest accuracy
Heidke Skill Score
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Performance above random
01Band Selector
Eren Bostan·[TAL-601]add per-band backtest chart panels

Band-Level Backtest Charts

Accuracy
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ROC-AUC
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HSS
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Null Model
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Degradation
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Yearly Accuracy & ROC-AUC — M4–5
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Confusion Matrix (Total)
TP
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FP
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FN
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TN
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Algorithm Info
Algorithm—
ROC-AUC—
F1 Score—
Accuracy
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ROC-AUC
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HSS
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Null Model
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Degradation
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Yearly Accuracy & ROC-AUC — M5–6
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Confusion Matrix (Total)
TP
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FP
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FN
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TN
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Algorithm Info
Algorithm—
ROC-AUC—
F1 Score—
Accuracy
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ROC-AUC
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HSS
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Null Model
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Degradation
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Yearly Accuracy & ROC-AUC — M6–7
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Confusion Matrix (Total)
TP
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FP
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FN
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TN
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Algorithm Info
Algorithm—
ROC-AUC—
F1 Score—
Accuracy
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ROC-AUC
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HSS
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Null Model
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Degradation
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Yearly Accuracy & ROC-AUC — M7+
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Confusion Matrix (Total)
TP
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FP
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FN
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TN
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Algorithm Info
Algorithm—
ROC-AUC—
F1 Score—
Skill Score

What is the Heidke Skill Score (HSS)?

HSS measures how much better a model performs compared to random guessing. It is the standard reference metric in operational earthquake forecasting systems.

HSS = 2(ad − bc) / [(a+c)(c+d) + (a+b)(b+d)]

a = TP  |  b = FP  |  c = FN  |  d = TN  — computed from the full confusion matrix.

HSS < 0Worse than random
HSS = 0Equal to random
HSS > 0Better than random
HSS = 1Perfect
02Year-by-Year Comparison
Defne Yilmaz·[TAL-602]plot all four bands yearly accuracy

4 Bands — Yearly Accuracy

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03Model History
Eren Bostan·[TAL-603]render model retraining timeline

Retraining Timeline

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Scheduled Degradation Online Learning
Backtest runs automatically every Monday. The latest results will be displayed above.