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

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

Question #: 69
Topic #: 4

[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?

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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Cecily

2 months ago

Linear regression? For predicting death? That's a bit morbid, don't you think?

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3 months ago

I agree, logistic regression is the way to go. It's a powerful tool for medical and healthcare applications.

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Delisa

1 months ago

D: Logistic regression is versatile and can be applied to various scenarios, making it a valuable tool for data analysis.

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Tyisha

2 months ago

C: It's great for predicting probabilities, especially in fields like medicine and social sciences.

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Lang

2 months ago

B: Definitely! Logistic regression is widely used in predicting outcomes based on observed characteristics.

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Elise

2 months ago

A: I agree, logistic regression is the way to go. It's a powerful tool for medical and healthcare applications.

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3 months ago

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

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