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Databricks Certified Professional Data Scientist Exam - Topic 1 Question 42 Discussion

Actual exam question for Databricks's Databricks Certified Professional Data Scientist exam
Question #: 42
Topic #: 1
[All Databricks Certified Professional Data Scientist Questions]

Logistic regression is a model used for prediction of the probability of occurrence of an event. It makes use of several variables that may be......

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Suggested Answer: C

by Justine at May 29, 2023, 07:08 PM

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Cherry
5 months ago
That's interesting, I didn't know it worked with categories too!
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Stephania
5 months ago
Yup, C is the right choice!
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Gilbert
6 months ago
Wait, are you sure about that? I thought it was just for numerical data.
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Nickolas
6 months ago
Totally agree, it's super versatile.
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Melodie
6 months ago
Logistic regression can handle both numerical and categorical variables!
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Pearly
6 months ago
I’m a bit confused about this one. I thought it was mostly for numerical data, but now I’m not so sure after reviewing the material.
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Paris
6 months ago
I feel like I read somewhere that logistic regression is flexible with input types, so maybe it really does use both numerical and categorical variables.
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Nina
6 months ago
I think I came across a practice question that emphasized how categorical variables are important in logistic regression, so I’m leaning towards option C.
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Tasia
6 months ago
I remember that logistic regression can handle both types of variables, but I'm not entirely sure if it was just one or both that are used.
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Stefania
6 months ago
I'm a little confused by the wording of the answers. Aren't all of these things that corrective actions can do? I'll have to think this through carefully.
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Stefania
6 months ago
Hmm, this seems pretty straightforward. I'll need to remember the key artifacts created by the JeOS tool - the system image, any optional images, and the README and vm.cfg files.
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Diane
11 months ago
Logistic regression is like a magician's hat - it can pull out both numerical and categorical rabbits!
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Dallas
10 months ago
D) None of the 1 and 2 are correct
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Mozell
10 months ago
C) Both 1 and 2 are correct
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Janet
10 months ago
B) Categorical
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Coleen
10 months ago
A) Numerical
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Avery
11 months ago
Ah, a trick question! The answer is obvious - logistic regression can work with both numerical and categorical variables. Easy peasy!
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Lashandra
9 months ago
C) Both 1 and 2 are correct
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Eva
10 months ago
B) Categorical
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Lonny
10 months ago
A) Numerical
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Barb
11 months ago
Hmm, let me think... Logistic regression definitely supports both types of predictor variables. This is a well-known fact in the field of machine learning.
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Jamal
10 months ago
Absolutely, having the flexibility to work with both types of variables makes logistic regression a versatile tool in data analysis.
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Otis
10 months ago
That's correct. It's one of the reasons why logistic regression is a popular choice for predictive modeling.
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Vincent
10 months ago
Absolutely, having the flexibility to work with both types of variables makes logistic regression a powerful tool for prediction.
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Providencia
11 months ago
Yes, you're right. Logistic regression can handle both numerical and categorical variables.
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Josphine
11 months ago
That's correct! It's one of the reasons why logistic regression is widely used in predictive modeling.
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Karon
11 months ago
Yes, logistic regression can handle both numerical and categorical predictor variables.
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Boris
12 months ago
Ah, this is a classic question. I'm pretty sure the correct answer is C - both numerical and categorical variables can be used in logistic regression.
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Chery
10 months ago
No problem, happy to help clarify things.
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Hollis
10 months ago
That's interesting, I didn't know that. Thanks for sharing!
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Velda
10 months ago
Yes, you're right. Logistic regression can use both numerical and categorical variables.
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Tien
11 months ago
I think the correct answer is C) Both 1 and 2 are correct.
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Nelida
11 months ago
It's important to understand the types of variables that can be used in different models.
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Helene
11 months ago
That's good to know. I always get confused with these types of questions.
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Marsha
11 months ago
Yes, you're right. Logistic regression can use both numerical and categorical variables.
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Loreta
11 months ago
I think the correct answer is C) Both 1 and 2 are correct.
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Mattie
12 months ago
Actually, I think the correct answer is C) Both 1 and 2 are correct because logistic regression can use both numerical and categorical variables.
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Amie
12 months ago
I disagree, I believe the answer is B) Categorical.
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Mattie
12 months ago
I think the answer is A) Numerical.
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Gilberto
12 months ago
Of course, logistic regression can handle both numerical and categorical variables! How else would we be able to model complex real-world scenarios?
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Franchesca
11 months ago
Of course, logistic regression can handle both numerical and categorical variables! How else would we be able to model complex real-world scenarios?
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Jolene
11 months ago
C) Both 1 and 2 are correct
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Chau
11 months ago
B) Categorical
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Novella
11 months ago
A) Numerical
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Wynell
12 months ago
Actually, I think the correct answer is C) Both 1 and 2 are correct because logistic regression can use both numerical and categorical variables.
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Crista
1 year ago
I disagree, I believe the answer is B) Categorical.
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Wynell
1 year ago
I think the answer is A) Numerical.
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