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Salesforce ANC-201 Exam - Topic 5 Question 11 Discussion

After the initial creation of a model, the first model insight explains93% of the variation of the outcome variable. This is unusually high.What is the most likely reason for this?
A) The dataset contains multiple dominant values.
B) The model contains too many outlier values.
C) The outcome variable may be causing data leakage.

Salesforce ANC-201 Exam - Topic 5 Question 11 Discussion

Actual exam question for Salesforce's ANC-201 exam
Question #: 11
Topic #: 5
[All ANC-201 Questions]

After the initial creation of a model, the first model insight explains

93% of the variation of the outcome variable. This is unusually high.

What is the most likely reason for this?

Show Suggested Answer Hide Answer
Suggested Answer: A

https://help.salesforce.com/articleView?id=bi_security_datasets_row_level.htm

https://help.salesforce.com/articleView?id=managing_the_sharing_model.htm&type=5

by Mirta at Jan 08, 2023, 11:29 AM

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Freeman
8 months ago
Totally agree, data leakage makes the most sense here.
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Rachael
9 months ago
Could be the dataset has dominant values.
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Kristel
9 months ago
Really? 93% seems too good to be true.
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Hyun
9 months ago
I think it's probably data leakage.
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Dong
9 months ago
That's a crazy high percentage!
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Thurman
9 months ago
I feel like I've seen something similar before, but I'm not confident about which option is the best. Maybe I should lean towards data leakage?
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Ezekiel
9 months ago
This reminds me of a practice question where we talked about dominant values. I wonder if option A could be relevant too.
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Venita
9 months ago
I'm not entirely sure, but I think having too many outliers could skew the results, making option B a possibility.
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Jeannetta
10 months ago
I remember discussing data leakage in class, and it seems like option C could be a strong contender here.
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Kelvin
10 months ago
I'm a bit confused by this question. Is it asking about the primary purpose of encryption in cloud object storage? I'll have to review my notes on cloud security to answer this one.
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Paris
10 months ago
This seems straightforward. The question is clearly asking about the maximum one-way latency, so option D, 150 ms one-way, is the correct answer.
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Mila
1 year ago
Wow, 93%? That's like winning the data modeling lottery! I'm hoping the answer is 'The model is so good, it should be illegal.'
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Cristy
1 year ago
A) The dataset contains multiple dominant values.
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Allene
1 year ago
C) The outcome variable may be causing data leakage.
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Gracia
1 year ago
B) The model contains too many outlier values.
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Hoa
1 year ago
A) The dataset contains multiple dominant values.
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Tien
1 year ago
Hey, if I can get 93% variation explained, I'm taking it and running! Doesn't matter how, I'm acing this exam, baby!
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Vivan
1 year ago
C) The outcome variable may be causing data leakage.
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Barabara
1 year ago
B) The model contains too many outlier values.
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Shaquana
1 year ago
A) The dataset contains multiple dominant values.
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Cristal
1 year ago
Data leakage, for sure. It's the only option that makes sense given how high the variation explained is. Someone's been peeking at the test answers!
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Cristina
1 year ago
C) The outcome variable may be causing data leakage.
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In
1 year ago
B) The model contains too many outlier values.
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Cherelle
1 year ago
A) The dataset contains multiple dominant values.
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Dexter
1 year ago
Multiple dominant values, huh? That could definitely skew the results. Gotta watch out for those sneaky outliers too.
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Fernanda
1 year ago
Outliers can throw off the whole model too.
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Rochell
1 year ago
Yeah, multiple dominant values can really mess things up.
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Kimi
1 year ago
But what if the outcome variable is causing data leakage? That could also be a reason.
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Dyan
1 year ago
Wow, 93% variation explained? That's insanely high! My money's on data leakage, it's the most likely culprit here.
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Lacey
1 year ago
I agree, data leakage seems like the most probable reason.
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Bev
1 year ago
C) The outcome variable may be causing data leakage.
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Edda
1 year ago
B) The model contains too many outlier values.
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Renea
1 year ago
A) The dataset contains multiple dominant values.
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Alaine
1 year ago
I agree with Selma. That could explain the high variation explained by the model.
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Selma
1 year ago
I think the dataset contains multiple dominant values.
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