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In this classroom discussion, the teacher asks the students to explain data leakage and its challenges. A student describes data leakage as the inclusion of information in the training data that would not be available in the real world. The student further explains that data leakage is challenging because it is often difficult to identify and can result in models that perform poorly in real-life scenarios. The student then provides a simple analogy of studying for a test based on specific information, only to realize that the actual exam doesn’t cover that information. The teacher acknowledges the analogy and relates it to the concept of overfitting and poor performance on unseen data

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