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iSQI Exam CT-AI Topic 8 Question 21 Discussion

Actual exam question for iSQI's CT-AI exam
Question #: 21
Topic #: 8
[All CT-AI Questions]

Which of the following is an example of a clustering problem that can be resolved by unsupervised learning?

Show Suggested Answer Hide Answer
Suggested Answer: A

Clustering is a form of unsupervised learning, which groups data points based on similarities without predefined labels. According to ISTQB CT-AI Syllabus, clustering is used in scenarios where:

The objective is to find natural groupings in data.

The dataset does not have labeled outputs.

Patterns and structures need to be identified automatically.

Analyzing the answer choices:

A . Associating shoppers with their shopping tendencies Correct

Shoppers can be grouped based on purchasing behaviors (e.g., luxury shoppers vs. budget-conscious shoppers), which is a typical clustering application in market segmentation.

B . Grouping individual fish together based on their types of fins Incorrect

If the types of fins are labeled, it becomes a classification problem, which requires supervised learning.

C . Classifying muffin purchases based on packaging attractiveness Incorrect

Classification, not clustering, because attractiveness scores or labels must be predefined.

D . Estimating the expected purchase of cat food after an ad campaign Incorrect

This is a prediction task, best suited for regression models, which are part of supervised learning.

Thus, Option A is the best answer, as clustering is used to group shoppers based on tendencies without predefined labels.

Certified Tester AI Testing Study Guide Reference:

ISTQB CT-AI Syllabus v1.0, Section 3.1.2 (Unsupervised Learning - Clustering and Association)

ISTQB CT-AI Syllabus v1.0, Section 3.3 (Selecting a Form of ML - Clustering).


Contribute your Thoughts:

Jamal
4 days ago
I'm voting for Option B, because who doesn't love a good fin-tastic clustering problem? It's like a fish version of 'Six Degrees of Kevin Bacon', but with more gills and less Hollywood.
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Martina
6 days ago
I think D) Estimating cat food purchases after an ad campaign is also a valid clustering problem.
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Cassie
7 days ago
I see your point, but I think C) Classifying muffin purchases based on packaging attractiveness is a better example.
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Gregoria
13 days ago
Option D all the way! Estimating cat food purchases after a successful ad campaign? That's like predicting how many hairballs a cat will produce after a nap. Unsupervised learning at its finest!
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Whitley
4 days ago
A) Associating shoppers with their shopping tendencies
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Colette
17 days ago
Hmm, this is a toughie. But I think Option C is the winner. Classifying muffins based on their packaging? That's like a beauty pageant for baked goods. Definitely an unsupervised learning problem.
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Effie
19 days ago
I'm gonna have to go with Option A on this one. Associating shoppers with their buying habits is a perfect example of an unsupervised learning task. It's like a digital version of people-watching, but with more math!
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Daniel
1 days ago
B) Grouping individual fish together based on their types of fins
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Lillian
5 days ago
That's a great choice! It's all about finding patterns in the data without any predefined labels.
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Ben
8 days ago
A) Associating shoppers with their shopping tendencies
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Joanna
23 days ago
I disagree, I believe it's B) Grouping individual fish together based on their types of fins.
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Amber
26 days ago
Option B seems like the obvious choice here. Grouping fish by their fin types is a classic clustering problem that can be solved with unsupervised learning. Easy peasy!
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Lashaunda
4 days ago
It's definitely a classic example, grouping fish by their fin types is a perfect fit for unsupervised learning.
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Raymon
15 days ago
I agree, option B is the best example of a clustering problem for unsupervised learning.
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Gaston
28 days ago
I think the answer is A) Associating shoppers with their shopping tendencies.
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