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2.2.1. Features and Labels
The Most Fundamental ML Concept:
| Term | Definition | Role | Example |
|---|---|---|---|
| Feature | Input variable used for prediction | Independent variable (X) | Age, weight, income, square footage |
| Label | Value being predicted | Dependent variable (Y) | Price, category, probability |
Visual: Features and Labels
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Example Analysis: "Predict e-scooter battery usage based on weather temperature and whether it's a weekday"
- Features: Weather temperature, weekday/weekend (these are INPUTS)
- Labels: Battery levels, distance traveled, number of hires (these are PREDICTIONS)
⚠️ Common Exam Trap: Questions often list several items and ask which are features vs. labels. Features are what you KNOW; labels are what you're trying to PREDICT.