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Answer: Grouping data points into similar clusters, also known as segmentation.
Linear regression is primarily used for predicting a numeric target by establishing a linear relationship between one or more independent variables and a numeric outcome. This is different from classification, which categorizes data into types or classes (Option A), and clustering, which groups data points into similar clusters based on features (Option B). Since the correct purpose of linear regression is not related to any form of classification or segmentation into clusters, the other options are not appropriate. Thus, the correct answer is Option B.
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What is the primary purpose of linear regression in machine learning, and how does it differ from classification and clustering?
A
Determining the category, type, or class of an item or data row.
B
Grouping data points into similar clusters, also known as segmentation.
C
Developing algorithms that use features of individual items to find similarities.
D
Applying clustering to demographics for grouping similar people or using text analysis to categorize sentences by topic or sentiment.
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