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SAS A00-240 Exam - Topic 4 Question 80 Discussion

An analyst knows that the categorical predictor, zip_code, is an important predictor of a binary target. However, zip_code has too many levels to be a feasible predictor in a model. The analyst uses PROC CLUSTER to implement Greenacre's method to reduce the number of categorical levels.What is the correct application of Greenacre's method in this situation?
D) Clustering the levels using dummy coded zip_code levels as inputs.
A) Clustering the levels using the target proportion for each zip_code as input.
B) Clustering the levels using the zip_code values as input.
C) Clustering the levels using the number of cases in each zip_code as input.

SAS A00-240 Exam - Topic 4 Question 80 Discussion

Actual exam question for SAS's A00-240 exam
Question #: 80
Topic #: 4
[All A00-240 Questions]

An analyst knows that the categorical predictor, zip_code, is an important predictor of a binary target. However, zip_code has too many levels to be a feasible predictor in a model. The analyst uses PROC CLUSTER to implement Greenacre's method to reduce the number of categorical levels.

What is the correct application of Greenacre's method in this situation?

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Suggested Answer: D

by Alecia at Jan 26, 2024, 10:49 PM

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Brandon
10 months ago
D sounds complicated, but could work if done right!
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Abel
10 months ago
C is interesting, but I think A is more relevant here.
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Willow
10 months ago
Wait, can you really cluster using just zip_code values?
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Frederica
10 months ago
I disagree, B seems more straightforward.
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Solange
10 months ago
A is the way to go! Target proportions matter.
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Arlette
11 months ago
I vaguely recall that using dummy variables could complicate the clustering process, so I'm leaning towards option A for this one.
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Linn
11 months ago
I practiced a similar question where we clustered based on case counts, but I think that might not be the best approach here either.
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Leoma
11 months ago
I'm not entirely sure, but I feel like clustering based on the zip_code values themselves might not capture the target's influence effectively.
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Johnson
11 months ago
I remember discussing how Greenacre's method focuses on the relationships between categories, so I think using the target proportion for each zip_code makes sense.
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Reuben
11 months ago
I'm pretty confident that the correct answer is A. Clustering the levels using the target proportion for each zip_code makes the most sense to reduce the number of levels while preserving the predictive power of the variable.
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Essie
11 months ago
I'm a bit confused on this one. Clustering the levels using the zip_code values or the number of cases doesn't seem quite right. Dummy coding the zip_code levels also doesn't seem relevant here.
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Jamal
11 months ago
Okay, the key here is that we're trying to reduce the number of levels in the zip_code predictor. I think using the target proportion for each zip_code as the input to the clustering makes the most sense.
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Dell
11 months ago
This looks like a tricky question. I'll need to think carefully about the different options and how Greenacre's method works.
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Olene
11 months ago
Hmm, this seems like a tricky one. I'll need to carefully review the options and think through the implications of each setting.
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Dick
11 months ago
This seems straightforward - I think the answer is to assign the existing service appointment to the crew.
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Johnetta
12 months ago
I remember calculating probabilities before, but I'm not completely sure how to approach this one with different ball colors.
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Matthew
1 year ago
I don't know, guys. Greenacre's method sounds a bit like rocket science to me. Maybe we should just ask the professor for the answer key.
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Carrol
1 year ago
D) Clustering the levels using dummy coded zip_code levels as inputs.
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Curt
1 year ago
C) Clustering the levels using the number of cases in each zip_code as input.
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Marion
1 year ago
B) Clustering the levels using the zip_code values as input.
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Rana
1 year ago
A) Clustering the levels using the target proportion for each zip_code as input.
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Isaac
1 year ago
Ah, the number of cases in each zip_code, the classic approach. I like it, nice and straightforward.
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Ashlee
1 year ago
C) Clustering the levels using the number of cases in each zip_code as input.
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Olive
1 year ago
B) Clustering the levels using the zip_code values as input.
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Tish
1 year ago
A) Clustering the levels using the target proportion for each zip_code as input.
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Sage
1 year ago
I'm not sure about using dummy coded zip_code levels as inputs. Doesn't that seem a bit like overkill for this problem?
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Margo
1 year ago
C) Clustering the levels using the number of cases in each zip_code as input.
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Shenika
1 year ago
I agree, using dummy coded zip_code levels might be too complex for this situation.
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Leah
1 year ago
I think using the target proportion for each zip_code makes more sense.
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Vincent
1 year ago
B) Clustering the levels using the zip_code values as input.
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Alishia
1 year ago
B) Clustering the levels using the zip_code values as input.
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Youlanda
1 year ago
A) Clustering the levels using the target proportion for each zip_code as input.
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Ligia
1 year ago
A) Clustering the levels using the target proportion for each zip_code as input.
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Willetta
1 year ago
Clustering the levels using the zip_code values as input? That's a bold move, Cotton. Let's see if it pays off.
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Sena
1 year ago
D) Clustering the levels using dummy coded zip_code levels as inputs.
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Caitlin
1 year ago
C) Clustering the levels using the number of cases in each zip_code as input.
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Maricela
1 year ago
B) Clustering the levels using the zip_code values as input.
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Lenna
1 year ago
A) Clustering the levels using the target proportion for each zip_code as input.
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William
1 year ago
I'm not sure, but I think C) Clustering the levels using the number of cases in each zip_code as input could also be a valid approach.
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Tabetha
1 year ago
Hmm, I think option A is the way to go. Using the target proportion for each zip_code as input seems like the most logical approach to cluster the levels.
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Oneida
1 year ago
I think so too. It's important to consider the target proportion when clustering the levels.
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Alesia
1 year ago
I think so too. It's important to consider the target proportion when clustering the levels.
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Bernadine
1 year ago
I agree, option A makes the most sense. It takes into account the target proportion for each zip_code.
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Ena
1 year ago
I agree, option A makes the most sense. It takes into account the target proportion for each zip_code.
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Malinda
1 year ago
I disagree, I believe it should be D) Clustering the levels using dummy coded zip_code levels as inputs.
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Rolande
1 year ago
I think the correct application is A) Clustering the levels using the target proportion for each zip_code as input.
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Ty
1 year ago
I agree with Layla, A) makes more sense because we want to reduce the number of levels based on the target variable.
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Emily
1 year ago
I disagree, I believe it should be D) Clustering the levels using dummy coded zip_code levels as inputs.
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Layla
1 year ago
I think the correct application is A) Clustering the levels using the target proportion for each zip_code as input.
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