Labeled data is called "labeled" because it includes a target feature/variable, which is usually what we want to predict.

Question

BlackTom AI · Accepted Answer

Labeled data includes a target variable (the "label") that represents the ground-truth outcome we aim to predict, so the statement is True.

1) Relevant knowledge points and concepts
- Labeled data vs. unlabeled data: Labeled datasets pair input features (predictors) with an output variable (label). Unlabeled data contains only inputs.
- Supervised learning: Uses labeled data to learn a mapping from inputs to the target label (classification/regression).
- Target feature/variable: The column or attribute in the dataset that holds the value to be predicted during model training and evaluation.

2) Step-by-step reasoning
- Definition: A dataset is described as labeled when each example has an associated label (target value).
- Purpose: The label provides the supervisory signal (ground truth) so an algorithm can adjust parameters to reduce prediction error.
- Typical workflow: Collect features X and labels y → train model f(X) ≈ y → evaluate on held-out labeled examples.
- Common examples: In MNIST, images (features) are paired with digit labels (0–9). In housing price prediction, property attributes are paired with a sale price label.

3) Calculations
- Not applicable here because this is definitional rather than numeric; no arithmetic steps are required.

4) Why the correct answer is correct
- The phrase “labeled data” literally refers to the presence of labels (target feature/variable). The statement that it “includes a target feature/variable, which is usually what we want to predict” matches standard machine learning terminology and practice.

5) Why the other option is incorrect
- "False" would imply labeled data does not include a target variable, contradicting the definition. That makes "False" incorrect.

6) Conclusion
Therefore, the correct response is True, matching the provided answer.

Labeled data is called "labeled" because it includes a target feature/variable, which is usually what we want to predict.判断题

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