# Data Leakage Prevention

> Runtime-enforced evaluate/assess boundary that rejects repeated test-set assessment.

- **Category**: Data Science
- **Subcategory**: Data Quality
- **Canonical URL**: https://designpattern.fyi/patterns/data_leakage_prevention/

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## Description
**Context**: Data leakage affected 294 published papers across 17 scientific fields. The grammar decomposes the supervised learning lifecycle into kernel primitives with hard constraints that reject leakage classes at call time.


## Use Cases
When building supervised ML systems to ensure that evaluation metrics are not artificially inflated.



## Implementation Example

```python
# Data Leakage Prevention
class EvidenceType: pass
# Runtime guard prevents test data in training
```



## Trade-offs


### Advantages

- - Prevents selection leakage

- - Prevents memorization leakage

- - Runtime enforcement




### Considerations & Drawbacks

- - Additional complexity

- - Requires strict typing of data flows







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**Reference**: [Original Source](https://arxiv.org/abs/2603.10742)