Databricks Certified Professional Data Scientist Exam - Topic 4 Question 18 Discussion

Actual exam question for Databricks's Databricks Certified Professional Data Scientist exam

Question #: 18
Topic #: 4

[All Databricks Certified Professional Data Scientist Questions]

Consider the following confusion matrix for a data set with 600 out of 11,100 instances positive:

In this case, Precision = 50%, Recall = 83%, Specificity = 95%, and Accuracy = 95%.

Select the correct statement

APrecision is low, which means the classifier is predicting positives best

BPrecision is low, which means the classifier is predicting positives poorly

Cproblem domain has a major impact on the measures that should be used to evaluate a classifier within it

D1 and 3

E2 and 3
In this case, Precision = 50%, Recall = 83%, Specificity = 95%: and Accuracy = 95%. In this case, Precision is low, which means the classifier is predicting positives poorly. However, the three other measures seem to suggest that this is a good classifier. This just goes to show that the problem domain has a major impact on the measures that should be used to evaluate a classifier within it, and that looking at the 4 simple cases presented is not sufficient.

Show Suggested Answer

Suggested Answer: E

by Malcolm at May 06, 2022, 03:18 AM

Limited Time Offer

25%

Off

Get Premium Databricks Certified Professional Data Scientist Questions as Interactive Web-Based Practice Test or PDF

Contribute your Thoughts:

Submit Cancel

Lashawn

4 months ago

Wait, 50% precision and 95% accuracy? That sounds off!

upvoted 0 times

...

Zita

4 months ago

I think the problem domain really matters here.

upvoted 0 times

...

Ivan

4 months ago

But isn't accuracy still high? Seems confusing.

upvoted 0 times

...

Barney

4 months ago

Totally agree, that means it's predicting positives poorly.

upvoted 0 times

...

Dalene

5 months ago

Precision is definitely low at 50%.

upvoted 0 times

...

Edelmira

5 months ago

I’m a bit confused about the relationship between precision and the other metrics. It seems like a good classifier overall, but the low precision is throwing me off.

upvoted 0 times

...

Julie

5 months ago

I think I saw a similar question where low precision meant poor positive predictions, so I'm leaning towards option E.

upvoted 0 times

...

Jolene

5 months ago

I remember practicing with confusion matrices, and I think a low precision indicates that the classifier is not doing well with positive predictions.

upvoted 0 times

...

Taryn

5 months ago

I'm not entirely sure, but I feel like option C makes sense because the context really matters when evaluating classifiers.

upvoted 0 times

...

Natalya

5 months ago

I'm a little confused by the mention of MPLS protection mechanisms in option C. That doesn't seem directly related to the EFM standard, so I'm not sure I should select that one.

upvoted 0 times

...

Chu

5 months ago

I'm a little confused by the wording of these options. I'll need to re-read them carefully to make sure I understand the differences between them before selecting an answer.

upvoted 0 times

...

Richelle

5 months ago

I'm not totally sure, but I feel like option A might not describe a transformational leader either. They focus more on attributes beyond just personality, right?

upvoted 0 times

...