CertNexus AIP-210 Exam - Topic 6 Question 38 Discussion

Actual exam question for CertNexus's AIP-210 exam

Question #: 38
Topic #: 6

The graph is an elbow plot showing the inertia or within-cluster sum of squares on the y-axis and number of clusters (also called K) on the x-axis, denoting the change in inertia as the clusters change using k-means algorithm.

What would be an optimal value of K to ensure a good number of clusters?

Show Suggested Answer

Suggested Answer: B

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by Rosalind at Feb 09, 2025, 02:15 AM

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Wade

10 months ago

Totally agree, K=3 looks optimal on the plot!

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Elfrieda

10 months ago

Really? I thought K=9 would be better for detail.

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Eric

11 months ago

Definitely K=2, it's the simplest option!

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Nydia

11 months ago

I think K=5 gives more granularity.

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Vilma

11 months ago

K=3 is usually the sweet spot!

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Major

11 months ago

I practiced a question like this before, and I think the answer was 3, but I’m worried I might be mixing it up with another example.

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Carissa

12 months ago

I feel like 2 clusters might be too few, but I can't recall if 9 is too many. I need to visualize the graph better.

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Lilli

12 months ago

I think the optimal K is usually where the inertia starts to level off, which might be around 3 or 5 based on similar practice questions we did.

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Dorsey

12 months ago

I remember we discussed the elbow method in class, but I'm not entirely sure how to identify the elbow point on the graph.

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Ronald

12 months ago

This seems straightforward enough. The elbow plot is showing the point where adding more clusters doesn't significantly reduce the inertia, so the optimal number is the "elbow" point. I'd go with option B, 3 clusters.

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Jerilyn

12 months ago

Okay, I think I've got this. The optimal number of clusters is the value of K where the elbow or "knee" in the plot occurs, indicating the point of diminishing returns. Based on the plot, I'd say the answer is C, 5 clusters.

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Carman

12 months ago

I'm a bit confused by this question. The elbow plot is showing the relationship between inertia and the number of clusters, but I'm not sure how to interpret that to determine the optimal number of clusters. I'll need to review my notes on k-means clustering to figure this out.

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Lindy

1 year ago

Hmm, this looks like a classic elbow plot question. I'll need to carefully analyze the plot to identify the point where the inertia starts to level off, that should give me the optimal number of clusters.

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Shantay

1 year ago

Hmm, the elbow plot seems to be telling us something, but I'm just too busy thinking about my next snack break to figure it out. I'll go with C) 5 and hope for the best. *munches on a cookie*

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Yolando

1 year ago

Ooh, I love a good elbow plot! I think 2 clusters would be the best choice here. After all, sometimes less is more, and who doesn't love a good ol' binary classification? *grins*

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Shawnda

1 year ago

I believe 9 clusters would be the best option for a more granular analysis.

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Hoa

1 year ago

I would go with 5 clusters to have a more detailed segmentation.

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Rosio

1 year ago

I think 3 clusters might be better to capture more variation in the data.

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Shayne

1 year ago

I agree with you, 2 clusters seem like the optimal choice.

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Dylan

1 year ago

Ah, the age-old question of how many clusters is enough. Based on the elbow plot, I'd say 9 clusters would be the way to go. Go big or go home, am I right? *chuckles*

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Chery

1 year ago

I'm not sure, but I think 3 clusters could also work well.

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Helaine

1 year ago

I agree, 5 clusters seems like a good balance.

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Carlota

1 year ago

I think 9 clusters might be too many, maybe 5 would be better.

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Donette

1 year ago

Hmm, I'm not sure. The elbow plot can be a bit tricky to interpret. I'm gonna go with 5 just to be safe. More clusters means more insights, right? *winks*

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Mirta

1 year ago

User 3: Yeah, I think 5 is a good option to ensure we have enough clusters for analysis.

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Shannan

1 year ago

User 2: I agree, 5 seems like a safe bet for a good number of clusters.

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Iesha

1 year ago

User 1: I think 5 is a good choice. More clusters can give us more insights.

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Eric

1 year ago

I think the optimal value of K would be 3. The elbow plot shows a clear bend in the curve at K=3, indicating that adding more clusters beyond that point doesn't significantly improve the inertia.

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