Data Lineage
Machine Learning
The inadvertent inclusion of information during training that would not be available during real-world prediction.
Detailed Explanation
Data leakage occurs when information from outside the training dataset improperly influences the model, leading to overly optimistic performance estimates. It often happens when data used for training includes future or irrelevant information that wouldn't be available in real-world scenarios. This compromises the model's validity, causing it to perform poorly on new, unseen data and undermining its generalization capability.
Use Cases
- •Detecting data leakage ensures model robustness before deployment by preventing overly optimistic performance estimates and improving real-world predictive accuracy.
Related Terms
Other terms in the Machine Learning category