Snowflake DSA-C02 Exam - Topic 1 Question 22 Discussion

Actual exam question for Snowflake's DSA-C02 exam

Question #: 22
Topic #: 1

[All DSA-C02 Questions]

Which method is used for detecting data outliers in Machine learning?

AScaler

BZ-Score

CBOXI

DCMIYC

Show Suggested Answer

Suggested Answer: C

By using ethnicity as a sensitive field, and comparing disparity between selection rates and performance metrics for each ethnicity value, you can evaluate the fairness of the model.

by Catherin at Jul 04, 2024, 12:12 PM

Limited Time Offer

25%

Off

Get Premium DSA-C02 Questions as Interactive Web-Based Practice Test or PDF

Contribute your Thoughts:

Submit Cancel

Shonda

8 months ago

CMIYC? Sounds made up, is that even a real method?

upvoted 0 times

...

Chantay

8 months ago

Scalers are not for outlier detection, just normalization!

upvoted 0 times

...

Barabara

8 months ago

Wait, what's BOXI? Never heard of that one.

upvoted 0 times

...

Amie

8 months ago

Totally agree, Z-Score is reliable!

upvoted 0 times

...

Casey

8 months ago

Z-Score is a common method for outlier detection.

upvoted 0 times

...

Gwen

9 months ago

I’m leaning towards Z-Score too; it’s like a standard way to identify outliers based on standard deviations, right?

upvoted 0 times

...

Shalon

9 months ago

BOXI sounds familiar, but I can't recall if it's actually a method for outlier detection or something else.

upvoted 0 times

...

Thea

9 months ago

I remember practicing with a question about outliers, and I feel like Scaler was mentioned, but it doesn't seem right for this.

upvoted 0 times

...

Dorathy

9 months ago

I think Z-Score is the method we learned for detecting outliers, but I'm not completely sure if it's the only one.

upvoted 0 times

...

Glory

9 months ago

Ah, I remember this now! The Z-Score method is definitely the way to go for detecting outliers in machine learning datasets. Glad I brushed up on that before the exam.

upvoted 0 times

...

Gary

9 months ago

Okay, let me see. I think the Z-Score method is used to identify outliers by calculating the standard deviation from the mean. That sounds right, but I'll double-check my notes just to be sure.

upvoted 0 times

...

Mozell

9 months ago

I'm pretty sure the answer is Z-Score, that's the method we learned for detecting outliers in the machine learning module.

upvoted 0 times

...

Hoa

9 months ago

Hmm, I'm a bit unsure on this one. I know we covered outlier detection, but I can't quite remember the specific method. I'll have to think this through carefully.

upvoted 0 times

...

Sarina

9 months ago

I'm a bit confused on this one. The options seem to cover different aspects of the TOGAF process, but I'm not sure which one specifically relates to the Preliminary Phase.

upvoted 0 times

...

Lashawn

1 year ago

B) Z-Score is the way to go. Anything else and you'll be z-scoring your way out of this exam!

upvoted 0 times

Yuonne

1 year ago

B) Yeah, Z-Score is the way to go. It's a reliable method for sure.

upvoted 0 times

...

Yolande

1 year ago

A) Scaler might work too, but Z-Score is more commonly used.

upvoted 0 times

...

Deonna

1 year ago

B) Z-Score is definitely the best method for detecting outliers.

upvoted 0 times

...

Fabiola

1 year ago

Haha, I thought D) CMIYC stood for 'Catch Me If You Can' at first. Gotta keep those outliers on their toes, you know!

upvoted 0 times

Delila

1 year ago

C) BOXI is not a method used for detecting data outliers.

upvoted 0 times

...

Alise

1 year ago

Haha, I thought D) CMIYC stood for 'Catch Me If You Can' at first. Gotta keep those outliers on their toes, you know!

upvoted 0 times

...

Barrett

1 year ago

B) Z-Score is another method used for detecting data outliers.

upvoted 0 times

...

Louis

1 year ago

A) Scaler is used for detecting data outliers in Machine learning.

upvoted 0 times

...

Phillip

1 year ago

C) BOXI and D) CMIYC? Really? Those sound more like secret agent code names than ML techniques. Nice try, exam writer!

upvoted 0 times

...

Vicente

1 year ago

I was confused between A) Scaler and B) Z-Score, but Z-Score makes more sense for outlier detection.

upvoted 0 times

Caprice

1 year ago

Yes, Z-Score is a statistical method that measures how far a data point is from the mean in terms of standard deviations.

upvoted 0 times

...

Frederica

1 year ago

I agree, Z-Score is commonly used for detecting outliers in Machine learning.

upvoted 0 times

...

Alberta

1 year ago

B) Z-Score is the correct answer for detecting data outliers in Machine Learning. It's a standard technique to identify data points that deviate significantly from the mean.

upvoted 0 times