Databricks Exam Databricks-Certified-Professional-Data-Scientist Topic 6 Question 75 Discussion

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

Question #: 75
Topic #: 6

[All Databricks-Certified-Professional-Data-Scientist Questions]

A fruit may be considered to be an apple if it is red, round, and about 3" in diameter. A naive Bayes classifier considers each of these features to contribute independently to the probability that this fruit is an apple, regardless of the

APresence of the other features.

BAbsence of the other features.

CPresence or absence of the other features

DNone of the above
In simple terms, a naive Bayes classifier assumes that the value of a particular feature is unrelated to the presence or absence of any other feature, given the class variable. For example, a fruit may be considered to be an apple if it is red, round, and about 3' in diameter A naive Bayes classifier considers each of these features to contribute independently to the probability that this fruit is an apple, regardless of the presence or absence of the other features.

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Suggested Answer: B, C

by Lettie at Nov 12, 2024, 11:37 PM

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Angella

4 days ago

This question is so apple-ling, I can't even. But I'm glad I now know the correct answer, or I'd be in a real jam.

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Matthew

9 days ago

Wait, so the classifier doesn't even consider if the fruit has a worm in it? That's some serious fruit discrimination if you ask me!

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Letha

10 days ago

Hmm, I was a bit unsure about this one. But now it makes sense - the classifier doesn't care if the apple is also juicy or has a stem, as long as it's red, round, and 3 inches wide.

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Malissa

12 days ago

Ah, I see! So, it's like saying the fruit's color doesn't depend on whether it's round or not. That's a pretty neat assumption for a classifier to make.

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Clorinda

15 days ago

But wouldn't the presence or absence of other features affect the probability of the fruit being an apple?

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Becky

16 days ago

The correct answer is C) Presence or absence of the other features. A naive Bayes classifier assumes that each feature contributes independently to the probability of the class variable, regardless of the presence or absence of the other features.

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Pansy

18 days ago

I disagree, I believe the answer is C) Presence or absence of the other features.

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Clorinda

21 days ago

I think the answer is A) Presence of the other features.

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