Salesforce ANC-201 Exam - Topic 2 Question 49 Discussion

Actual exam question for Salesforce's ANC-201 exam

Question #: 49
Topic #: 2

A CRM Analytics consultant is reviewing results from an Einstein Discovery story with a business user. They agree with the findings but notice that none of the fields used in the story have a correlation value greater than 4%. The client is now concerned that the model

may not be good enough to deploy.

Which action should the consultant take?

AA Identify additional data that may have a stronger relationship with the outcome variable.

BEdit the model accuracy settings and rerun it to evaluate the correlation.

CUse the appropriate algorithm and update the model.

Show Suggested Answer

Suggested Answer: A

by Timothy at Oct 24, 2024, 02:00 AM

Limited Time Offer

25%

Off

Get Premium ANC-201 Questions as Interactive Web-Based Practice Test or PDF

Contribute your Thoughts:

Submit Cancel

Sina

3 months ago

Using a better algorithm could make a big difference!

upvoted 0 times

...

Rolland

3 months ago

Wait, can just changing settings really fix this?

upvoted 0 times

...

Terrilyn

3 months ago

I think editing the model settings might help too.

upvoted 0 times

...

Candida

4 months ago

Totally agree, they should look for more relevant data!

upvoted 0 times

...

Jettie

4 months ago

Correlation values under 4% are pretty low.

upvoted 0 times

...

Shawnta

4 months ago

I’m a bit confused about the best approach. Should we really focus on the algorithm, or is it more important to find better data? I wish I could remember more from our last session.

upvoted 0 times

...

Marge

4 months ago

This reminds me of a practice question where we had to choose between updating the model or finding new data. I feel like using the appropriate algorithm could be key here.

upvoted 0 times

...

Novella

4 months ago

I'm not entirely sure, but I think editing the model accuracy settings might not actually solve the underlying issue with the data.

upvoted 0 times

...

Camellia

5 months ago

I remember we discussed how low correlation values can indicate that the model might not be capturing the right relationships. I think identifying additional data could be a good first step.

upvoted 0 times

...

Valene

5 months ago

For this type of question, I'd probably go with option A. Identifying additional data with stronger relationships to the outcome seems like the best way to strengthen the model and address the client's concerns.

upvoted 0 times

...

Margo

5 months ago

I'm a bit confused by this one. The low correlation values are concerning, but I'm not sure if editing the model accuracy settings is the right approach. Maybe I'd start by exploring option A.

upvoted 0 times

...

Fausto

5 months ago

Okay, so the correlation values are really low. I'm thinking option A might be the way to go - see if I can find some additional data that could improve the model.

upvoted 0 times

...

Donette

5 months ago

Hmm, this is a tricky one. I'd want to look into getting more relevant data to see if I can find stronger predictors for the outcome.

upvoted 0 times

...

Caitlin

1 year ago

Hmm, I'd say a combination of A and C. Get better data and try different algorithms. Kinda like a cuWynellry expert - can't make a delicious dish with mediocre ingredients!

upvoted 0 times

Gerald

1 year ago

That sounds like a solid plan. Better data and smarter algorithms could definitely improve the model.

upvoted 0 times

...

Melinda

1 year ago

That makes sense. Better data and smarter algorithms could definitely improve the model.

upvoted 0 times

...

Becky

1 year ago

C) Use the appropriate algorithm and update the model.

upvoted 0 times

...

Tayna

1 year ago

C) Use the appropriate algorithm and update the model.

upvoted 0 times

...

Chantay

1 year ago

B) Edit the model accuracy settings and rerun it to evaluate the correlation.

upvoted 0 times

...

Dorathy

1 year ago

A) Identify additional data that may have a stronger relationship with the outcome variable.

upvoted 0 times

...

Denny

1 year ago

A) Identify additional data that may have a stronger relationship with the outcome variable.

upvoted 0 times

...

Nobuko

1 year ago

I'd go for option B. Tweaking the model settings could unlock hidden insights that the consultant might have missed. Who knows, the correlation might just be higher than it seems.

upvoted 0 times

Reed

1 year ago

Business User: Agreed, let's give it a go and see if the model improves.

upvoted 0 times

...

Chandra

1 year ago

Consultant: It's worth a shot to uncover any hidden insights.

upvoted 0 times

...

Wynell

1 year ago

Business User: Sounds like a good idea, let's see if the correlation improves.

upvoted 0 times

...

Jules

1 year ago

Consultant: Let's try editing the model accuracy settings and rerun it.

upvoted 0 times

...

Wynell

1 year ago

Option C sounds promising. The consultant should try a different algorithm to see if that improves the model performance. Sometimes the default algo just doesn't cut it.

upvoted 0 times

...

Glory

1 year ago

Definitely option A. The model needs better input variables to make accurate predictions. Increasing the model accuracy settings won't help if the core data is weak.

upvoted 0 times

Ulysses

1 year ago

User 4: Updating the model with appropriate algorithm could also help in this situation.

upvoted 0 times

...

An

1 year ago

User 3: Let's focus on improving the input variables for better predictions.

upvoted 0 times

...

Salome

1 year ago

User 2: Agreed, increasing the model accuracy settings won't help if the core data is weak.

upvoted 0 times

...

Santos

1 year ago

User 1: I think we should identify additional data that may have a stronger relationship with the outcome variable.

upvoted 0 times

...

Fairy

1 year ago

I agree, we need stronger relationships for better results.

upvoted 0 times

...

Joni

1 year ago

I think the consultant should go for option A. We can't make a good model without strong predictors. The client is right to be concerned about the low correlation.

upvoted 0 times