Databricks Exam Databricks-Certified-Professional-Data-Scientist Topic 4 Question 69 Discussion

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

Question #: 69
Topic #: 4

[All Databricks Certified Professional Data Scientist Exam 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?

ALinear regression

BK-means clustering

CLogistic regression

DApriori algorithm
Logistic regression is used widely in many fields, including the medical and social sciences. For example, the Trauma and Injury Severity Score (TRISS), which is widely used to predict mortality in injured patients, was originally developed by Boyd et al. using logistic regression. Many other medical scales used to assess severity of a patient have been developed using logistic regression. Logistic regression may be used to predict whether a patient has a given disease (e.g. diabetes; coronary heart disease), based on observed characteristics of the patient (age, sex, body mass index, results of various blood tests, etc.; age, blood cholesterol level, systolic blood pressure, relative weight, blood hemoglobin level, smoking (at 3 levels), and abnormal electrocardiogram.).Another example might be to predict whether an American voter will vote Democratic or Republican, based on age, income, sex, race, state of residence, votes in previous elections, etc. The technique can also be used in engineering, especially for predicting the probability of failure of a given process, system or product. It is also used in marketing applications such as prediction of a customer's propensity to purchase a product or halt a subscription, etc.[citation needed] In economics it can be used to predict the likelihood of a person's choosing to be in the labor force, and a business application would be to predict the likelihood of a homeowner defaulting on a mortgage. Conditional random fields, an extension of logistic regression to sequential data, are used in natural language processing.

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Suggested Answer: C

by Chara at Sep 19, 2024, 06:20 PM

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21 days ago

Logistic regression seems like the obvious choice here. Predicting probability of an outcome based on multiple risk factors is exactly what it's designed for.

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Trinidad

4 days ago

B: Absolutely, logistic regression is commonly used in various fields for this type of prediction.

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Pamella

7 days ago

A: I agree, logistic regression is definitely the way to go for predicting probability based on multiple risk factors.

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Sol

21 days ago

I think the most appropriate method for this project is C) Logistic regression.

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