Why should you care?

AIPredict fraud model trained pre-holiday may degrade when transaction patterns shift.

See it live — copy this example

Use a .NET console or Web API project with Microsoft.ML. Run dotnet run after pasting.

var baseline = JsonSerializer.Deserialize<MetricSnapshot>(File.ReadAllText("models/fraud-v12.metrics.json"));
var current = EvaluateProductionSample(recentRows, model);
var aucDrop = baseline.AreaUnderRocCurve - current.AreaUnderRocCurve;
if (aucDrop > 0.05)
    await alerts.SendAsync($"Drift: AUC dropped {aucDrop:F3} vs champion");

What happened?

• Store champion metrics at train time; re-evaluate labeled sample from production; alert on metric delta.
• Follow the steps below — typing the code yourself is the fastest way to learn.

Practice next

1. Save baseline metrics.json.
2. Eval recent labeled sample.
3. Alert if AUC drop > threshold.
4. Track feature mean shift on Amount.
5. Auto-open retrain ticket on drift.

Remember

Baseline vs current metrics. Labeled prod sample. Threshold alerts.

AIPredict fraud drift

Post-holiday AUC falls 0.07 vs baseline.

Outcome: Retrain job triggered same day.