Data Leakage

Data Leakage - In the context of AI, data leakage refers to the introduction of information into the training data that the system is expected to infer but should not legitimately have access to during model training. This results in a model that appears to perform well during evaluation on the test set but demonstrates poor performance during deployment when evaluated on new data sets.

Class Information

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Identification

Label (rdfs)
Data Leakage
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Alternative Labels
Data Contamination, Model Contamination, Unintended Data Inclusion
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Definition and Examples

Definition
In the context of AI, data leakage refers to the introduction of information into the training data that the system is expected to infer but should not legitimately have access to during model training. This results in a model that appears to perform well during evaluation on the test set but demonstrates poor performance during deployment when evaluated on new data sets.
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