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When is clustering appropriate to use?

Answer and explanation

Correct answer: When groups of similar customers need to be identified

Clustering is an unsupervised learning method that forms groups of data points with similar characteristics without predefined class labels. Therefore, it is suitable for identifying groups of similar customers based on features such as purchasing behaviour. Option B refers to classification, where the correct class of each example is already known.

Related tags

ClusteringCustomer SegmentationUnsupervised LearningOrange Data MiningMachine Learning Basics

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