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Databricks Exam Databricks Certified Professional Data Scientist Topic 3 Question 64 Discussion

Actual exam question for Databricks's Databricks Certified Professional Data Scientist exam
Question #: 64
Topic #: 3
[All Databricks Certified Professional Data Scientist Questions]

Select the correct statement regarding the naive Bayes classification

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Suggested Answer: A

by Edward at Jul 09, 2024, 10:48 PM

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Zita
2 days ago
I agree, B is also correct since independence is assumed.
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Laquita
8 days ago
A is definitely true, it needs less data!
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Junita
14 days ago
I feel like D is too complicated for naive Bayes since it simplifies things by not needing the entire covariance matrix.
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Gail
19 days ago
I practiced a question similar to this, and I recall that only variances need to be determined, which makes C seem likely.
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Mitzie
24 days ago
I’m not entirely sure, but I think B about independent variables being assumed is a key feature of naive Bayes.
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Vallie
1 month ago
I remember that naive Bayes is often praised for needing less training data, so I think A might be correct.
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Sherell
1 month ago
Okay, let me think this through. Naive Bayes assumes independence between the features, which simplifies the calculations. And it only requires estimating means and variances for each class, not the full covariance matrix. I believe I can apply that knowledge to select the right answer.
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Stephanie
1 month ago
Ah yes, I remember learning about naive Bayes in class. The fact that it only needs to calculate variances per class instead of the full covariance matrix is a big advantage in terms of computational efficiency. I'm confident I can identify the correct statement here.
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Christiane
1 month ago
Hmm, I'm a bit unsure about this one. I know naive Bayes makes some strong assumptions, but I can't quite recall all the details. I'll need to review my notes on the key characteristics of this classifier before attempting to answer.
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Bernardo
1 month ago
This looks like a straightforward question on the key assumptions and requirements of the naive Bayes classifier. I'll focus on remembering the main points - it needs little training data, assumes independent variables, and only requires calculating variances per class rather than the full covariance matrix.
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Arleen
1 month ago
This is a straightforward question about exit status codes. I'm pretty confident the answer is A - the process ended without any problems.
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Ressie
1 month ago
I vaguely recall something about being consistent in responses to resistance, but was that really part of Lewin's original model?
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Dong
6 months ago
Hold up, is this a trick question or something? I feel like I'm about to fall down a rabbit hole of statistical jargon. Time to bust out the calculator!
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Elenore
6 months ago
Ah, the old 'small amount of training data' trick! That's gotta be the answer. I bet the person who wrote this question is a real comedian.
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Domonique
5 months ago
C) only the variances of the variables for each class need to be determined
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Lai
5 months ago
B) Independent variables can be assumed
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Kenneth
6 months ago
A) it only requires a small amount of training data to estimate the parameters
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Jesusita
6 months ago
Hmm, this is a tricky one. I've heard about the whole 'covariance matrix' thing, but it's like trying to untangle a bowl of spaghetti in my brain.
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Bambi
5 months ago
C) only the variances of the variables for each class need to be determined
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Meaghan
5 months ago
B) Independent variables can be assumed
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Carin
6 months ago
A) it only requires a small amount of training data to estimate the parameters
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Judy
6 months ago
Alright, let's see here... I think option B is the way to go. Independent variables, that's the key, right? Easy peasy!
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Pamella
7 months ago
Wow, this question is a real head-scratcher! I'm not sure I've got the whole 'naive Bayes' thing down pat, but I'm gonna give it my best shot.
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Bobbie
6 months ago
Yes, that's correct. Only the variances of the variables for each class need to be determined
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Pauline
6 months ago
So, independent variables can be assumed in naive Bayes, right?
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Mammie
6 months ago
B) Independent variables can be assumed
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Major
6 months ago
That's right! Naive Bayes is great because it doesn't need a lot of data for training
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Junita
6 months ago
I think the correct statement is A) it only requires a small amount of training data to estimate the parameters
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Norah
6 months ago
A) it only requires a small amount of training data to estimate the parameters
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Dortha
7 months ago
Yes, because independent variables are assumed, only the variances of the variables for each class need to be determined
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Cassie
7 months ago
I agree with Clare, that's an advantage of naive Bayes classification
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Clare
7 months ago
I think the correct statement is A) it only requires a small amount of training data to estimate the parameters
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