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What is the name of the method that transforms categorical features into a series of binary indicator feature variables?
Suggested Answer: C
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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).
27 comments · newest first
VE
Veronica
10 months ago
Wait, are we sure it's not Target encoding?
BR
Breana
10 months ago
Agreed, that's the standard method.
GA
Gaston
10 months ago
It's definitely One-hot encoding!
SU
Susana
10 months ago
I thought it was Leave-one-out encoding at first.
NA
Na
10 months ago
One-hot is the way to go for categorical features!
LE
Leandro
11 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.
KA
Kaycee
11 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.
FI
Fidelia
11 months ago
I remember practicing a question about encoding techniques, and one-hot encoding was definitely mentioned there.
RO
Roy
11 months ago
I think the method we're looking for is one-hot encoding, but I'm not completely sure.
IS
Isadora
11 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.
TR
Trinidad
12 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.
AU
Audrie
12 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.
FE
Fernanda
1 year 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.
KR
Kristal
1 year 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.
KR
Krissy
1 year ago
This question is a no-brainer. C) One-hot encoding is the answer, hands down. It's like asking what 2 + 2 is.
PA
Paola
1 year ago
E) String indexing? What is this, the Stone Age? One-hot encoding is the modern solution.
MI
Mila
1 year ago
B) Target encoding is an interesting option, but I think C) One-hot encoding is the way to go here.
NI
Nicholle
1 year ago
D) Categorical? Really? That's not even an encoding method, just a data type.
CY
Cyril
1 year ago
Can't believe someone picked D. What were they thinking?
DE
Desmond
1 year ago
Exactly, C is the method we're looking for!
RO
Rosalind
1 year ago
C is the right pick, one-hot encoding is popular.
MA
Marleen
1 year ago
I thought D was a joke answer!
VI
Vivan
1 year ago
C) One-hot encoding, of course! This is a classic technique I've used countless times.
JO
Johnson
1 year ago
I remember learning about this in class. It's definitely C) One-hot encoding.
PA
Paulina
1 year ago
I'm not sure, but I'll go with C as well. It creates a binary variable for each category.
DE
Denae
1 year ago
I think it's C too. It's a common method used in machine learning.
RE
Reita
1 year ago
C) One-hot encoding