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CompTIA DY0-001 Exam - Topic 5 Question 18 Discussion

A data scientist is clustering a data set but does not want to specify the number of clusters present. Which of the following algorithms should the data scientist use?
A) DBSCAN
B) k-nearest neighbors
C) k-means
D) Logistic regression

CompTIA DY0-001 Exam - Topic 5 Question 18 Discussion

Actual exam question for CompTIA's DY0-001 exam
Question #: 18
Topic #: 5
[All DY0-001 Questions]

A data scientist is clustering a data set but does not want to specify the number of clusters present. Which of the following algorithms should the data scientist use?

Show Suggested Answer Hide Answer
Suggested Answer: A

DBSCAN discovers clusters based on density without requiring you to predefine the number of clusters, automatically finding arbitrarily shaped groups and identifying noise points.


by Sheridan at May 07, 2026, 11:35 AM

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Sharmaine
3 days ago
K-nearest neighbors isn't a clustering algorithm. Just a classification tool.
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Yong
9 days ago
I feel confident about DBSCAN. It’s flexible and efficient.
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Cecilia
14 days ago
Exactly! Logistic regression isn't even for clustering.
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Tiffiny
19 days ago
K-means requires the number of clusters. Not suitable here.
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Elsa
24 days ago
Agreed! DBSCAN handles noise well too.
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Kayleigh
29 days ago
I think DBSCAN is the best choice. It finds clusters without needing a preset number.
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Johnson
1 month ago
Not sure about that, k-nearest neighbors seems more reliable.
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Sharen
1 month ago
Wait, can DBSCAN really work without knowing the number of clusters?
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Shalon
1 month ago
Totally agree, DBSCAN handles varying cluster sizes well.
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Edelmira
2 months ago
I thought k-means was the standard for clustering?
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Merri
2 months ago
DBSCAN is the way to go for that!
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Erin
2 months ago
Logistic regression seems out of place here since it's more for classification, not clustering.
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Junita
4 months ago
I feel like I've seen a question like this before, and I think it was about density-based clustering, which points to DBSCAN.
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Elbert
4 months ago
I'm not entirely sure, but I remember k-means requires you to define the number of clusters, so it can't be the answer.
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Carlota
4 months ago
I think DBSCAN is the right choice since it can find clusters without needing to specify the number of them upfront.
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