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Pegasystems PEGACPDS88V1 Exam - Topic 6 Question 36 Discussion

Actual exam question for Pegasystems's PEGACPDS88V1 exam
Question #: 36
Topic #: 6
[All PEGACPDS88V1 Questions]

Prediction Studio supports keyword-based topic detection, model-based topic detection and the combination of these. When using machine learning,

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Suggested Answer: C

When using machine learning, the Must keywords function aspositive features.


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Azalee
2 months ago
Totally agree, Must keywords act as positive features!
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Lyndia
2 months ago
I think keywords have less impact than the training data.
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Anika
3 months ago
Wait, are you saying keywords are ignored? That seems off.
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Cassi
3 months ago
I’ve heard mixed things about the impact of keywords vs. training data.
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Antonio
3 months ago
Must keywords are definitely important for topic detection!
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Josphine
3 months ago
I vaguely remember that keywords shouldn't be ignored, but I can't remember the exact role they play in the model.
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Rebeca
4 months ago
I practiced a similar question, and I think Must keywords act as positive features in the model.
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Stevie
4 months ago
I feel like keywords might have a higher impact, but I can't recall if that's true compared to the training data.
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Dierdre
4 months ago
I think I remember that Must keywords are really important for topic detection, but I'm not sure if they are required.
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Noel
4 months ago
Hmm, I'm not sure about the difference between the Must keywords being required to detect the topic versus functioning as positive features. I'll need to think about that a bit more.
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Broderick
4 months ago
I'm pretty confident that the keywords are not ignored, since the question specifically mentions keyword-based topic detection. That rules out option D.
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Noah
5 months ago
Okay, let's think this through. The question is asking about the impact of keywords when using machine learning, so I'm going to focus on that and try to eliminate the options that don't seem to fit.
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Kenneth
5 months ago
This question seems straightforward, but I want to make sure I understand the concepts of keyword-based and model-based topic detection before selecting an answer.
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