Salesforce Exam ANC-301 Topic 8 Question 38 Discussion

Actual exam question for Salesforce's ANC-301 exam

Question #: 38
Topic #: 8

A training dataset Is being prepared for a Einstein Discovery story. One skewed with outliers. at action should the Einstein consultant take?

ARemove the outlier rows.

BNothing, because the field is not the outcome variable.

CChange the method of binning to fixed width.

DRemove the field because it has bad data

Show Suggested Answer

Suggested Answer: C

by Marguerita at Jul 16, 2024, 11:42 PM

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Nan

22 days ago

Removing outliers? Pffft, that's like trying to tame a wild Einstein. I say we just let the data do its thing!

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Kristofer

21 hours ago

B) Nothing, because the field is not the outcome variable.

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Amber

4 days ago

Removing outliers can help improve the accuracy of the model.

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Novella

10 days ago

A) Remove the outlier rows.

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Norah

23 days ago

Option D? Nah, that's just throwing the baby out with the bathwater. Let's fix the data, not discard it!

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Mary

23 hours ago

B) Nothing, because the field is not the outcome variable.

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Lelia

12 days ago

A) Remove the outlier rows.

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Sherell

1 months ago

I agree with Francisca, removing the outlier rows would be the best option.

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King

1 months ago

I'd go with C. Changing the binning method could help handle the skewed data better.

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Viva

1 months ago

I'm not sure, B seems reasonable too. If the field isn't the outcome variable, why bother with the outliers?

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Cammy

2 days ago

B) Nothing, because the field is not the outcome variable.

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Daisy

6 days ago

A) Remove the outlier rows.

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Isabelle

1 months ago

I disagree, I believe we should change the method of binning to fixed width.

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Arthur

1 months ago

Definitely option A. Removing outliers is crucial for a clean and reliable training dataset.

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Chaya

28 days ago

Outliers can really skew the data, so it's best to get rid of them.

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Vivan

1 months ago

I agree, removing outliers is important for accurate results.

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Francisca

2 months ago

I think we should remove the outlier rows.

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