I want to monitor distribution shift for top 5 important features in all fraud models across entire set
Keep top feature contributions consistent, ensuring your models deliver reliable ML predictions every time.
I want to monitor training-serving skew in 4 models across entire set
Quickly identify mismatches between training and production data to prevent accuracy degradation.
I want to monitor input drift for all entities in all fraud models across all segments comparing last week to same period last month
Keep your models performing optimally by detecting dataset shifts in real-time.
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Easily get started with a free
community edition account.
!pip install superwise
import superwise as sw
project = sw.project("Fraud detection")
model = sw.model(project,"Customer a")
policy = sw.policy(model,drift_template)
Entire population drift – high probability of concept drift. Open incident investigation →
Segment “tablet shoppers” drifting. Split model and retrain.
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