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Databricks Certified Professional Data Scientist Exam - Topic 4 Question 30 Discussion

Actual exam question for Databricks's Databricks Certified Professional Data Scientist exam
Question #: 30
Topic #: 4
[All Databricks Certified Professional Data Scientist Questions]

Refer to the exhibit.

You are using K-means clustering to classify customer behavior for a large retailer. You need to determine the optimum number of customer groups. You plot the within-sum-of-squares (wss) data as shown in the exhibit. How many customer groups should you specify?

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Suggested Answer: C

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Maryanne
4 months ago
Not sure about this... 8 seems like too many groups to me.
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Evangelina
4 months ago
Definitely 3, the drop in wss is clear there.
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Brynn
4 months ago
Wait, why is everyone saying 3? I thought 2 was enough!
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Raina
4 months ago
I think 4 might actually be better for more granularity.
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Cathrine
4 months ago
Looks like 3 is the sweet spot based on the elbow method!
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Trina
5 months ago
I’m leaning towards option B, but I’m not 100% confident. I wish I had more practice with interpreting these types of plots.
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Rhea
5 months ago
I feel like 4 groups might be too many, but I can't quite remember how to justify that. The graph looks like it flattens out around 3, right?
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Markus
5 months ago
I think we practiced a similar question where we had to choose the number of clusters based on the wss graph. If I recall correctly, the optimal number is where the decrease in wss starts to level off.
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Kristin
5 months ago
I remember we discussed the elbow method in class, but I'm not entirely sure how to identify the elbow point in this plot.
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Stefanie
5 months ago
I'm a little confused on this one. I thought the Scrum Daily Meeting could be held at different times, as long as it's consistent. Is there a specific "most encouraged" time? I'll have to review my notes.
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Willis
5 months ago
This is a tricky one. The solution sounds good, but I'm not sure if it's a complete justification for choosing Okta. I'll need to consider other factors like security, scalability, and cost to determine if Okta is the best fit.
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