Oracle Exam 1Z0-1110-23 Topic 5 Question 23 Discussion

Actual exam question for Oracle's 1Z0-1110-23 exam

Question #: 23
Topic #: 5

As a data scientist, you are working on a global health data set that has data from more than 50 countries. You want to encode three features, such as 'countries', 'race', and 'body organ' as categories. Which option would you use to encode the categorical feature?

ADataFramLabelEncode()

Bauto_transform()

COneHotEncoder()

Dshow_in_notebook()

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Suggested Answer: A

by Amira at Jul 02, 2024, 01:11 PM

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Dustin

4 months ago

Wow, this is a tough one. I'm torn between B) auto_transform() and C) OneHotEncoder(). Maybe I should just flip a coin... or better yet, just ask the cat. They always have the answers.

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Ressie

4 months ago

D) show_in_notebook()? Really? I think that's more for visualizing data than encoding categorical features. C) OneHotEncoder() is the clear winner here. It's like the Swiss Army knife of categorical encoding.

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Bulah

4 months ago

Ah, the age-old dilemma of categorical feature encoding. I'd have to say C) OneHotEncoder() is the way to go. It may be a bit more work, but it ensures you don't lose any valuable information. Plus, it's way more fun to say than DataFramLabelEncode().

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5 months ago

I'd go with C) OneHotEncoder(). It's the perfect choice for encoding multiple categorical features without losing information. Plus, it's a classic go-to in the data science world.

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Nida

4 months ago

I think OneHotEncoder() is the most efficient option for encoding multiple categorical features in this case.

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Marge

5 months ago

I agree, OneHotEncoder() is definitely the way to go for encoding categorical features.

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