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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?

ADBSCAN

Bk-nearest neighbors

Ck-means

DLogistic regression

Show Suggested 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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Shalon

10 hours ago

Totally agree, DBSCAN handles varying cluster sizes well.

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Edelmira

6 days ago

I thought k-means was the standard for clustering?

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Merri

11 days ago

DBSCAN is the way to go for that!

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Erin

16 days ago

Logistic regression seems out of place here since it's more for classification, not clustering.

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Junita

2 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

2 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

2 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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