Databricks Certified Professional Data Scientist Exam - Topic 2 Question 7 Discussion

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

Question #: 7
Topic #: 2

[All Databricks Certified Professional Data Scientist Questions]

You are having 1000 patients' data with the height and age. Where age in years and height in meters. You wanted to create cluster using this two attributes. You wanted to have near equal effect for both the age and height while creating the cluster. What you can do?

AYou will be adding height with the numeric value 100

BYou will be converting each height value to centimeters

CYou will be dividing both age and height with their respective standard deviation

DYou will be taking square root of height
When you see the data age in years would have values like 50, 60r 70 90 years etc. And while calculating distance from centroid maximum possible value can be 90-0 and its square will be 8100.
While using heights in meter can be 2-0.5(1.5) meters and its square will be 2.25 only. So you can see age has more effect than height. Hence bringing the height on same level you can convert it into centimeters. Can bring data upto 200 centimeters and then it be more effective like square of 200 maximum.
However there is another approach is to divide the each value with its standard deviation, which will not have impact of the units e.g. age/sd of the age, which results in value without unit. This can also help in reducing the effect of units.

Show Suggested Answer

Suggested Answer: B, C

by Elza at May 04, 2022, 07:07 PM

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Jettie

4 months ago

Definitely agree with standard deviation for equal effect!

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Johnna

4 months ago

Wait, square root of height? That seems weird...

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Herschel

4 months ago

Adding 100 to height? That sounds off.

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Leandro

4 months ago

Dividing by standard deviation is the way to go!

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Clarinda

5 months ago

I think converting height to centimeters makes sense!

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Grover

5 months ago

I’m a bit confused about the square root option. It seems like it wouldn’t really help with the scale issue between age and height.

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Jesus

5 months ago

I’m not entirely sure, but I think converting height to centimeters could help balance the scales. It makes sense since age values are much larger.

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Essie

5 months ago

I remember we discussed normalizing data to ensure both attributes have equal weight. Dividing by standard deviation sounds familiar.

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Marti

5 months ago

I feel like we practiced a similar question where we had to standardize variables. Dividing by standard deviation seems like a solid approach.

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Artie

5 months ago

I'm pretty sure the Catalyst 3560-CX and Catalyst 4500-E are the two products supported as Extended in DNA-C 1.1, but I'll double-check the details to be sure.

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Lashaunda

5 months ago

The --single-transaction option suggests this is a consistent backup, but I'm not sure about the other statements. I'll need to review the documentation to be confident in my answers.

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Lynda

5 months ago

Option D looks like it covers a good range, but I'm uncertain if it has an effective representation of the tiers we studied.

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