Discuss CompTIA DY0-001 Exam Topic 5 Question 18

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

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.

Get Premium DY0-001 Questions as Interactive Web-Based Practice Test or PDF Real Exam Format Detailed Explanations Instant Access Get Your Practice Test

21 comments · newest first

Adria 18 days ago

Right! Plus, it’s great for large datasets.

Madelyn 23 days ago

I feel confident about DBSCAN. It handles noise well.

Eric 28 days ago

Exactly! Logistic regression isn't even for clustering.

Edison 1 month ago

K-means is out for this question. It needs the number of clusters specified.

Pok 1 month ago

Yeah, I agree! DBSCAN can find clusters of varying shapes too.

Sue 1 month ago

I think DBSCAN is the best choice here. It doesn't require the number of clusters.

Sharmaine 2 months ago

K-nearest neighbors isn't a clustering algorithm. Just a classification tool.

Yong 2 months ago

I feel confident about DBSCAN. It’s flexible and efficient.

Cecilia 2 months ago

Exactly! Logistic regression isn't even for clustering.

Tiffiny 2 months ago

K-means requires the number of clusters. Not suitable here.

Elsa 2 months ago

Agreed! DBSCAN handles noise well too.

Kayleigh 2 months ago

I think DBSCAN is the best choice. It finds clusters without needing a preset number.

Johnson 3 months ago

Not sure about that, k-nearest neighbors seems more reliable.

Sharen 3 months ago

Wait, can DBSCAN really work without knowing the number of clusters?

Shalon 3 months ago

Totally agree, DBSCAN handles varying cluster sizes well.

Edelmira 3 months ago

I thought k-means was the standard for clustering?

Merri 3 months ago

DBSCAN is the way to go for that!

Erin 4 months ago

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

Junita 5 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.

Elbert 5 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.

Carlota 5 months ago

I think DBSCAN is the right choice since it can find clusters without needing to specify the number of them upfront.

CompTIA DY0-001 Exam - Topic 5 Question 18 Discussion