Clustering is a supervised learning

Question

BlackTom AI · Accepted Answer

This question asks us to classify the statement about clustering as true or false.
Option 1: True. The claim 'Clustering is a supervised learning' would be incorrect because clustering is typically categorized as unsupervised learning. In supervised learning, models learn from labeled data where inputs are paired with target outputs. Clustering, by contrast, groups data based on similarity without using labeled outcomes, aiming to discover natural structure or patterns in the data.
Option 2: False. Saying clustering is not supervised aligns with standard definitions in machine learning. Since there are no predefined labels guiding the grouping, clustering falls under unsupervised learning. Its purpose is to reveal inherent data structure, such as clusters or segments, rather than to predict a known target variable.
In summary, the statement in Option 1 contradicts the fundamental distinction between supervised and unsupervised learning, and Option 2 correctly reflects that clustering is an unsupervised technique.

Clustering is a supervised learning

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Clustering is a supervised learning

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