Case context: A research group collects pictures of ripe and unripe apples from several orchards. It labels ripe fruit as class 1 and unripe fruit as class 0, but then leaves the whole collection unused because it thinks any dataset must be protected until the final check.

Question: What mistake has the group made, and how should it handle these pictures?

Sample answer: The group is mixing up data used for fitting a model with data used for judging it. The labeled apple pictures should be combined into a training collection so the model can learn from them and update its parameters. A separate test collection should be kept aside and used only after training to measure performance.

Key points:

• The collected pictures can be used as training data.
• Ripe apples are the positive class.
• Unripe apples are the negative class.
• The model should be fit using the training data.
• Test data should stay reserved for evaluation.

Rubric: The response should identify the confusion between training data and test data and explain that the labeled pictures belong in model fitting, while the test data must remain held out for evaluation.