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Databricks Machine Learning Associate Exam - Topic 1 Question 32 Discussion

What is the name of the method that transforms categorical features into a series of binary indicator feature variables?
C) One-hot encoding
A) Leave-one-out encoding
B) Target encoding
D) Categorical
E) String indexing

Databricks Machine Learning Associate Exam - Topic 1 Question 32 Discussion

Actual exam question for Databricks's Databricks Machine Learning Associate exam
Question #: 32
Topic #: 1
[All Databricks Machine Learning Associate Questions]

What is the name of the method that transforms categorical features into a series of binary indicator feature variables?

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Suggested Answer: C

The method that transforms categorical features into a series of binary indicator variables is known as one-hot encoding. This technique converts each categorical value into a new binary column, which is essential for models that require numerical input. One-hot encoding is widely used because it helps to handle categorical data without introducing a false ordinal relationship among categories. Reference:

Feature Engineering Techniques (One-Hot Encoding).


by Nelida at Jul 09, 2025, 01:19 AM

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Veronica
7 months ago
Wait, are we sure it's not Target encoding?
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Breana
7 months ago
Agreed, that's the standard method.
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Gaston
7 months ago
It's definitely One-hot encoding!
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Susana
7 months ago
I thought it was Leave-one-out encoding at first.
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Na
7 months ago
One-hot is the way to go for categorical features!
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Leandro
8 months ago
I’m a bit confused; I thought categorical encoding was a broader term that included one-hot encoding, but I can't recall the specifics.
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Kaycee
8 months ago
I feel like there was something about target encoding too, but it seems more related to the target variable than just transforming features.
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Fidelia
8 months ago
I remember practicing a question about encoding techniques, and one-hot encoding was definitely mentioned there.
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Roy
8 months ago
I think the method we're looking for is one-hot encoding, but I'm not completely sure.
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Isadora
8 months ago
One-hot encoding, that's the one! I remember learning about this in my machine learning class. It's a really useful technique for converting categorical features into a format that can be used in models.
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Trinidad
9 months ago
I'm a little confused by this question. There are a few different techniques for dealing with categorical data, like leave-one-out encoding and target encoding. I'm not 100% sure which one is being asked about here.
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Audrie
9 months ago
Okay, I think I've got this. The method that transforms categorical features into binary indicator variables is called one-hot encoding. That's definitely the right answer here.
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Fernanda
9 months ago
Hmm, I'm a bit unsure about this one. I know there are a few different ways to handle categorical features, but I can't quite remember the specific name for the method that creates binary indicator variables. I'll have to think this through carefully.
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Kristal
9 months ago
I'm pretty sure this is asking about one-hot encoding, which is a common technique for transforming categorical features into a format that can be used in machine learning models.
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Krissy
10 months ago
This question is a no-brainer. C) One-hot encoding is the answer, hands down. It's like asking what 2 + 2 is.
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Paola
10 months ago
E) String indexing? What is this, the Stone Age? One-hot encoding is the modern solution.
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Mila
10 months ago
B) Target encoding is an interesting option, but I think C) One-hot encoding is the way to go here.
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Nicholle
10 months ago
D) Categorical? Really? That's not even an encoding method, just a data type.
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Cyril
9 months ago
Can't believe someone picked D. What were they thinking?
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Desmond
9 months ago
Exactly, C is the method we're looking for!
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Rosalind
9 months ago
C is the right pick, one-hot encoding is popular.
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Marleen
10 months ago
I thought D was a joke answer!
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Vivan
10 months ago
C) One-hot encoding, of course! This is a classic technique I've used countless times.
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Johnson
11 months ago
I remember learning about this in class. It's definitely C) One-hot encoding.
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Paulina
11 months ago
I'm not sure, but I'll go with C as well. It creates a binary variable for each category.
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Denae
12 months ago
I think it's C too. It's a common method used in machine learning.
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Reita
12 months ago
C) One-hot encoding
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