Pegasystems Exam PEGACPDS88V1 Topic 1 Question 11 Discussion

Actual exam question for Pegasystems's PEGACPDS88V1 exam

Question #: 11
Topic #: 1

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

AAt least 100 fields to reach an acceptable level of model performance

BAll fields that have been predictive in the past

CAll available uncorrected fields

DUp to 100 fields to limit the impact on model speed

Show Suggested Answer

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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4 days 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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5 days 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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7 days 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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9 days 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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9 days ago

I agree with Paulene, having too many predictors can slow down the model.

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11 days ago

I think the answer is D) Up to 100 fields to limit the impact on model speed.

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