Question 1

Question

Question 1

BlackTom AI · Accepted Answer

Unsupervised learning groups unlabeled data into clusters or discovers structure without target labels, so option a is the correct description.

Relevant knowledge points:
- Unsupervised learning: finds patterns, structure, or clusters in data that have no labels (examples: k-means clustering, hierarchical clustering, PCA).
- Supervised learning: learns a mapping from inputs to known labeled outputs for prediction (examples: linear regression, decision trees, classification).
- Reinforcement learning: learns actions by trial and error using rewards/penalties to maximize cumulative reward (examples: Q-learning, policy gradients).
- Exhaustive search / brute-force: tries all possible solutions without relying on data-driven learning; not a standard ML paradigm.

Step-by-step reasoning:
1. Read option a: “Grouping unlabeled data into clusters without target labels.” This matches the definition of unsupervised learning exactly — clustering is a core unsupervised task.
2. Read option b: “Learning by trial and error through rewards and penalties.” That describes reinforcement learning, not unsupervised learning, so b is incorrect.
3. Read option c: “Exhaustively searching all possible solutions without using data.” This describes brute-force search, not any standard ML learning paradigm, so c is incorrect.
4. Read option d: “Learning from labeled examples to predict outputs for new inputs.” That is the textbook definition of supervised learning, so d is incorrect.

Why option a is correct:
- It explicitly mentions unlabeled data and clustering, which are fundamental to unsupervised methods. Algorithms like k-means partition data into clusters based only on feature similarities, with no labels provided during learning.

Why other options are incorrect (brief):
- b = reinforcement learning (uses rewards), not clustering.
- c = brute-force search (not a learning paradigm).
- d = supervised learning (requires labels).

Conclusion: The correct choice is a. Grouping unlabeled data into clusters without target labels, which matches the provided answer.

Question 1单项选择题

类似问题

What kind of machine learning setting is usually used for grouping?

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Which of the following is an example of unsupervised learning technique?

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Which scenario is MOST clearly unsupervised?

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