What is the importance of understanding data leakage in machine learning?

What is the importance of understanding data leakage in machine learning?

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

Can you give me an example of data leakage?

Sure! If a model is trained on a dataset that includes future information, like using test data to inform training, that's data leakage.

How can I prevent data leakage in my projects?

To prevent data leakage, ensure that your training and test datasets are completely separate and avoid using any future data during training.

What are the consequences of data leakage?

The main consequence is that the model may perform well on test data but fail in real-world scenarios, leading to poor decision-making.