check_leakage
Detect data leakage in datasets using column-name heuristics, high correlation to target, and time-based backfill patterns to prevent biased models.
Instructions
Three-layer leakage detection (Level 6).
Layer 1 (always): name heuristics — flags columns named like 'label_*',
'outcome_*', 'pred_*', 'post_*'. Layer 2 (with target): features whose
Pearson correlation with target > 0.95. Layer 3 (with target + time):
features that are constant within each time bucket but vary across
buckets (likely backfilled). Output size: small.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| source_id | Yes | ||
| time_column | No | ||
| target_column | No |
Output Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||