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Pegasystems Exam PEGACPDS88V1 Topic 1 Question 11 Discussion

Actual exam question for Pegasystems's PEGACPDS88V1 exam
Question #: 11
Topic #: 1
[All PEGACPDS88V1 Questions]

Configuring an adaptive model involves selecting the potential predictors. How many potential predictors are recommended for an adaptive model?

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Suggested Answer: A

As a data scientist, a valid reason to adjust the default response timeout in a prediction is tosuit the use case.


by Julio at May 08, 2024, 08:35 AM

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Novella
2 months ago
100 fields? That's a lot of data to crunch. I hope my computer can handle it, or I might as well just run the model by hand.
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Holley
8 days ago
D) Up to 100 fields to limit the impact on model speed
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Candida
20 days ago
100 fields does seem like a lot, but it's important for accuracy.
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Stephen
21 days ago
A) At least 100 fields to reach an acceptable level of model performance
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Nadine
2 months ago
Up to 100 fields? That's a lot, but at least it's a reasonable limit. I wonder how that impacts the model's performance and speed.
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Nieves
22 days ago
User 3: Nieves, that makes sense. It's important to balance performance and speed.
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Lettie
1 months ago
User 2: Lettie, I think it's to limit the impact on model speed.
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Keva
1 months ago
User 1: Up to 100 fields seems like a lot, but it's a reasonable limit.
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Laticia
3 months ago
Uncorrected fields? That sounds like a recipe for disaster. I'll have to do some more research on best practices for adaptive model configuration.
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Rhea
2 months ago
User 2: I agree, having too many uncorrected fields could definitely lead to issues. It's important to find the right balance.
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Raul
2 months ago
User 1: I think it's best to limit the potential predictors to up to 100 fields to maintain model speed.
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Casie
3 months ago
But wouldn't it be better to include all fields that have been predictive in the past for better accuracy?
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Norah
3 months ago
I'm not sure about using all fields that were predictive in the past. Shouldn't we focus on the most relevant ones for the current situation?
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France
2 months ago
D) Up to 100 fields to limit the impact on model speed
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Regenia
2 months ago
I agree, using all past predictors may not be the best approach for current situations.
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Sharee
2 months ago
B) All fields that have been predictive in the past
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Yaeko
2 months ago
A) At least 100 fields to reach an acceptable level of model performance
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Glory
3 months ago
Wow, 100 fields? That seems a bit excessive. I wonder if there's a more efficient way to configure an adaptive model.
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Bernardine
3 months ago
I agree with Paulene, having too many predictors can slow down the model.
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Paulene
3 months ago
I think the answer is D) Up to 100 fields to limit the impact on model speed.
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