What is data leakage in model training?

What is data leakage in model training?

Data leakage occurs when information from outside the training dataset is used to create the model, leading to overly optimistic performance.

Can you give me an example of data leakage?

Sure! An example would be if you include the target variable in your training features, which can lead to misleading results.

How can I prevent data leakage?

To prevent data leakage, ensure that your training and test datasets are properly separated and avoid using future information.

What are the consequences of data leakage?

The consequences include poor model generalization, misleading performance metrics, and ultimately, a model that fails in real-world applications.