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Databricks Exam Databricks Certified Professional Data Scientist Topic 6 Question 14 Discussion

Actual exam question for Databricks's Databricks Certified Professional Data Scientist exam
Question #: 14
Topic #: 6
[All Databricks Certified Professional Data Scientist Questions]

A data scientist wants to predict the probability of death from heart disease based on three risk factors: age, gender, and blood cholesterol level. What is the most appropriate method for this project?

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Suggested Answer: C

Contribute your Thoughts:

Buck
9 days ago
Surprised logistic regression is so versatile!
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Eun
14 days ago
K-means clustering doesn't even fit here!
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Shenika
20 days ago
Wait, why not linear regression? Seems simpler.
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Jani
25 days ago
I agree, it's perfect for binary outcomes.
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Nelida
1 month ago
Definitely logistic regression for this!
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Alonso
1 month ago
I recall logistic regression being used in medical studies, so it seems like the best fit for predicting heart disease outcomes.
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Stefania
1 month ago
K-means clustering feels off too; it’s more about grouping data rather than predicting probabilities, right?
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Aliza
1 month ago
I'm not entirely sure, but I remember something about linear regression being for continuous outcomes, so that doesn't seem right for this question.
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Santos
1 month ago
I think logistic regression is the right choice here since we're predicting a binary outcome, like death or survival.
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Tommy
1 month ago
Okay, let's see here. The company is financed by both equity and debt, so I'll need to consider methods that account for that capital structure. I'm pretty confident I can narrow it down to the 3 best options.
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Myong
1 month ago
I'm a bit unsure about this one. Does an Okta Sign-on Policy really handle the MFA requirement, or is there something else I should be considering?
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Santos
1 month ago
Hmm, this is a tricky one. I'll need to carefully analyze the test results to determine if the system update meets the 99% concurrency target.
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