Databricks Certified Professional Data Scientist Exam - Topic 4 Question 8 Discussion

Actual exam question for Databricks's Databricks Certified Professional Data Scientist exam

Question #: 8
Topic #: 4

[All Databricks Certified Professional Data Scientist Questions]

You are working with the Clustering solution of the customer datasets. There are almost 40 variables are available for each customer and almost 1.00,0000 customer's data is available. You want to reduce the number of variables for clustering, what would you do?

AYou will randomly reduce the number of variables

BYou will find the correlation among the variables and from their variables are not co-related will be discarded.

CYou will find the correlation among the variables and from the highly co-related variables, you will be considering only one or two variables from it.

DYou cannot discard any variable for creating clusters.

EYou can combine several variables in one variable
When you are applying clustering technique and you find that there are quite a huge number of variables are available. Then it is better the find the co-relation among the variables and consider only one or two variables from the highly co-related variables. Because highly co-related variable will have the same effect, while creating the cluster. We can use scatter plot matrix among the variables to find the co-relation.
You can also combine several variables into a single variable. For example if you have two values in the dataset like Asset and Debt than by combining these two values like Debt to Asset ratio and use it while creating the cluster.

Show Suggested Answer

Suggested Answer: C, E

by Diane at May 06, 2022, 11:39 PM

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Sage

3 months ago

Combining variables sounds smart, like creating a Debt to Asset ratio!

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Elden

3 months ago

Randomly reducing variables? That's a bad idea.

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Denny

3 months ago

Wait, can we really just discard variables? Seems risky!

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Javier

4 months ago

Totally agree, option C makes the most sense.

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Sherell

4 months ago

Correlation analysis is key for variable reduction!

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Carlton

4 months ago

I'm a bit confused about option D; I thought we could discard some variables to improve clustering efficiency.

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Lenna

4 months ago

I feel like I saw a similar question in our practice exams, and I think combining variables could be a good strategy, like in option E.

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Royal

4 months ago

I think option C makes sense because it focuses on keeping the most relevant variables by discarding highly correlated ones.

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Melda

5 months ago

I remember we discussed variable reduction techniques, but I'm not sure if randomly reducing variables is a good approach.

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Arleen

5 months ago

I'm a little unsure about the difference between "can be understood independently" and "contain no extraneous content." I'll need to think through those distinctions carefully.

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Gerry

5 months ago

I vaguely recall that using point-in-time recovery would only create a snapshot, and it might not meet the requirement for recovery in the same cluster, right?

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Gilma

5 months ago

Hmm, I'm a bit unsure about this one. The options seem similar, but I'll try to think through which one most accurately captures the idea of a successful solution.

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Jesusita

5 months ago

Ah, I've got this! The correct answer is option B - you register your app with the Android Backup Service using the tag in your app's manifest file. I'm confident in this approach.

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