Which scenario is MOST clearly unsupervised?

Question

BlackTom AI · Accepted Answer

Segmenting users into behavioral groups is a classic unsupervised learning task because it looks for structure in feature data without labeled target outcomes.

1) Relevant knowledge points and concepts
- Unsupervised learning: methods that find patterns, clusters, or low-dimensional structure in data when no ground-truth labels/targets are provided (examples: clustering, dimensionality reduction).
- Supervised learning: methods that map inputs to known outputs/labels (examples: regression, classification).
- Typical algorithms: k-means, hierarchical clustering, Gaussian mixture models, DBSCAN for clustering (unsupervised); linear regression, random forest regression, logistic regression, decision trees for supervised tasks.

2) Step-by-step reasoning
- Examine each option to see whether the task requires labeled outcomes:
  a) Segmenting users into behavioral groups: objective is to discover groups of similar users from features (clicks, session length, purchases) without a predefined label. This uses clustering — unsupervised.
  b) Predicting disease outcomes: you need known outcomes (e.g., diseased vs. healthy, survival time) as labels to train a model — supervised (classification or survival regression).
  c) Predicting house prices from features: you train against known sale prices (numeric targets) — supervised regression.
  d) Classifying emails as spam or not: requires labeled examples of spam vs. not spam — supervised classification.

3) Intermediate steps / logic checks
- For (a): no target variable is specified; you group by similarity — matches unsupervised definition.
- For (b)-(d): each explicitly implies predicting or classifying a target, thus requiring labeled data.

4) Why the correct answer is correct
- Segmenting users is “most clearly unsupervised” because it explicitly involves discovering natural groupings in unlabeled behavioral data. Clustering algorithms operate precisely in this setting.

5) Why other options are incorrect
- Predicting disease outcomes, house prices, and spam detection all require labeled targets and are therefore supervised tasks (classification or regression), not unsupervised.

Conclusion: The correct answer is "Segmenting users into behavioral groups," which matches the provided answer.

Which scenario is MOST clearly unsupervised?单项选择题

类似问题

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

Of the 3 main AI/machine learning techniques, the one that identifies clusters within a dataset without any pre-defined or labelled categories is an example of __________ learning.

Which of the following is used almost exclusively for pattern detection on unlabeled data where the system is not told what to look for specifically but to simply discover patterns in the data?

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

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

What is clustering?

Question 1

What is the main goal of unsupervised learning?

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