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Salesforce ANC-201 Exam - Topic 4 Question 30 Discussion

When deploying a model to an existing Prediction, w number should be considered"1
B) 10: Limit of number of models under a Prediction Definition.
A) 5: Limit of total number of Prediction Definitions.
C) 20: Limit of number of models under a Prediction Definition.
D) 3: Limit of total number of Models.

Salesforce ANC-201 Exam - Topic 4 Question 30 Discussion

Actual exam question for Salesforce's ANC-201 exam
Question #: 30
Topic #: 4
[All ANC-201 Questions]

When deploying a model to an existing Prediction, w number should be considered"1

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Suggested Answer: B

by Valentin at Mar 16, 2024, 05:28 PM

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Jules
8 months ago
I thought it was 10 too, but now I'm not so sure.
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Donte
8 months ago
I agree, 5 is the right number for total Prediction Definitions.
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Pansy
8 months ago
Wait, are we sure about the 3 models limit? Seems low.
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Katina
9 months ago
No way, it's actually 20 for that limit!
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Ivory
9 months ago
I think it's definitely 10 for the models under a Prediction Definition.
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Evangelina
9 months ago
I vaguely recall that there’s a limit of 3 total models, but that seems low compared to what we discussed in class.
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Elouise
9 months ago
I’m a bit confused; I thought the limit was 20 for models, but now I’m second-guessing myself.
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Kristeen
9 months ago
I practiced a question like this, and I feel like the limit for models under a Prediction Definition is 10.
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Arthur
9 months ago
I think I remember something about limits on Prediction Definitions, but I'm not sure if it's 5 or 10.
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Lisha
9 months ago
Hmm, I'm not entirely sure about this one. I'll make an educated guess, but I might need to come back to it if I'm still unsure.
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Junita
9 months ago
I'm a bit confused by the wording of this question. Can someone clarify what exactly a "Prediction" is in this context? I want to make sure I understand the concepts before answering.
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Laurel
9 months ago
I've got this! The question is asking about the limit on the number of models under a Prediction Definition, so the answer must be C.
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Gennie
10 months ago
Okay, let me see... I think the key here is understanding the difference between Prediction Definitions and individual Models. I'll need to review that before answering.
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Louis
10 months ago
Hmm, this seems like a tricky one. I'll need to think carefully about the limits and constraints around Predictions and Models.
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Celestina
10 months ago
Hmm, I'm a bit unsure about this one. The objective mentions protecting, controlling, and monitoring access to ePHI, so I'll need to think carefully about which safeguard category would cover that.
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Sherell
10 months ago
Hmm, I'm not too familiar with the differences between Type 1 and Type 2 hypervisors. I'll have to think this through carefully.
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Veronique
2 years ago
Hmm, that's a good point. I think C) 20 also makes sense now that I think about it.
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Devora
2 years ago
I'm not sure, but I think the answer might be B) 10 because it seems like a reasonable limit for the number of models.
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Fidelia
2 years ago
I disagree, I believe the answer is C) 20 because it makes more sense to have a higher limit for models under a Prediction Definition.
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Veronique
2 years ago
I think the answer is A) 5 because there is a limit on the total number of Prediction Definitions.
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Marya
2 years ago
Ooh, this one's tricky. I'm going to have to go with the classic B) 10 option. Anything higher seems a bit excessive, don't you think?
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Ben
2 years ago
Haha, I bet the answer is C) 20. Who would ever want to limit themselves to just 10 models? Go big or go home, am I right?
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Xenia
2 years ago
I agree with you, C) 20 does seem like a lot of models to have under one Prediction Definition.
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Margart
2 years ago
I would go with D) 3. It's better to have a smaller number of high-quality models than a bunch of mediocre ones.
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Bette
2 years ago
I agree, having too many models could get confusing. But I see your point about going big!
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Louisa
2 years ago
I think the answer is actually B) 10. It's a good balance between too few and too many models.
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Deja
2 years ago
I agree with you, I also think the answer is B) 10. It's a reasonable limit for models.
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Renea
2 years ago
I think the answer is B) 10. It's a good balance between too few and too many models.
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Micaela
2 years ago
I think the answer is actually B) 10. It's important to have a limit to keep things organized.
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Nieves
2 years ago
Hmm, that's a good point too. Having a higher limit could be beneficial for certain scenarios.
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Lindy
2 years ago
D) 3: Limit of total number of Models? That can't be right, there's gotta be more than that. I'm going with B).
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Candida
2 years ago
B) 10: Limit of number of models under a Prediction Definition.
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Emilio
2 years ago
A) 5: Limit of total number of Prediction Definitions.
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Eveline
2 years ago
Hmm, I was leaning towards C) 20, but I'm not totally sure. Guess I need to review my model deployment limits again.
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Lawanda
2 years ago
I think the answer is B) 10: Limit of number of models under a Prediction Definition. That makes the most sense to me.
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Ronald
2 years ago
Yes, that's correct. It's important to consider the limit of models when deploying a model to an existing Prediction.
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Helaine
2 years ago
I agree, B) 10: Limit of number of models under a Prediction Definition seems like the correct answer.
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Jaleesa
2 years ago
Actually, I believe the answer is C) 20, as it would allow for more flexibility and options when deploying a model.
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Shasta
2 years ago
I agree with it makes sense to have a limit on the number of models under a Prediction Definition.
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Nieves
2 years ago
I think the answer is B) 10, because there is a limit to the number of models under a Prediction Definition.
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