AI Associate AI Fundamentals Practice Question
Which type of machine learning is used to predict customer churn based on historical labeled data?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Supervised learning
Supervised learning uses labeled data (historical churn outcomes) to train a model to predict future churn.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Reinforcement learning
Why it's wrong here
Reinforcement learning learns through rewards/penalties in an environment, not from historical labeled data.
- ✗
Unsupervised learning
Why it's wrong here
Unsupervised learning finds patterns in unlabeled data, not suitable for predicting a specific label like churn.
- ✓
Supervised learning
Why this is correct
Supervised learning trains on labeled examples to predict outcomes, making it ideal for churn prediction.
- ✗
Self-supervised learning
Why it's wrong here
Self-supervised learning generates labels from data structure, but churn prediction typically uses explicit historical labels.
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