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Oracle Exam 1Z0-1122-23 Topic 3 Question 23 Discussion

Actual exam question for Oracle's 1Z0-1122-23 exam
Question #: 23
Topic #: 3
[All 1Z0-1122-23 Questions]

What is the difference between classification and regression in Supervised Machine Learning?

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Suggested Answer: A

Classification and regression are two subtypes of supervised learning in machine learning. The main difference between them is the type of output variable they deal with. Classification assigns data points to discrete categories based on some criteria or rules. For example, classifying emails into spam or not spam based on their content is a classification problem because the output variable is binary (spam or not spam). Regression predicts continuous values for data points based on their input features. For example, predicting house prices based on their size, location, amenities, etc., is a regression problem because the output variable is continuous (house price). Classification and regression use different types of algorithms and metrics to evaluate their performance.Reference::Oracle Cloud Infrastructure AI - Machine Learning Concepts,Classification vs Regression in Machine Learning | by ...


by Lyda at Jul 10, 2024, 04:06 AM

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Josue
10 months ago
I'm going with A. Gotta love those clear-cut definitions. Regression is for predicting numbers, classification is for sorting things into groups. Simple as that!
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Nettie
10 months ago
That's right! Classification is for categories and regression is for continuous values.
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Bernardine
10 months ago
A) Classification assigns data points to categories, whereas regression predicts continuous values.
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Blair
11 months ago
B) Classification and regression both predict continuous values? What is this, some kind of trick question? Everyone knows that's not true.
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Audria
10 months ago
A) Yes, exactly. Classification and regression serve different purposes in Supervised Machine Learning.
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Brynn
10 months ago
B) No, that's not true. Classification and regression are different. Classification assigns data points to categories, while regression predicts continuous values.
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Serina
10 months ago
A) Classification assigns data points to categories, whereas regression predicts continuous values.
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Von
11 months ago
So, classification and regression have different purposes in Supervised Machine Learning.
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Shayne
11 months ago
Yes, that's correct. Classification is for categories and regression is for continuous values.
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Marva
11 months ago
D) Classification and regression both assign data points to categories? Haha, that's a good one! Clearly the person who wrote that option doesn't know their machine learning basics.
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Claudio
11 months ago
Ah, I knew it! Classification is for categorical outcomes, and regression is for continuous ones. Easy peasy!
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Rory
10 months ago
No, actually classification assigns data points to categories while regression predicts continuous values.
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Beckie
10 months ago
B) Classification and regression both predict continuous values.
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Nilsa
10 months ago
Yes, that's correct! Classification is for categories and regression is for continuous values.
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Margot
10 months ago
A) Classification assigns data points to categories, whereas regression predicts continuous values.
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Kallie
11 months ago
I agree with Minna. Regression predicts continuous values, right?
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Myra
11 months ago
A) Classification assigns data points to categories, whereas regression predicts continuous values. This is the correct answer, it's a clear distinction between the two techniques.
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Haley
11 months ago
B) Classification and regression both predict continuous values.
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Olive
11 months ago
A) Classification assigns data points to categories, whereas regression predicts continuous values.
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Minna
11 months ago
I think the difference is that classification assigns data points to categories.
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