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What does a model primarily identify in unsupervised learning?

Answer and explanation

Correct answer: Hidden groups or patterns in unlabeled data

In unsupervised learning, the data is not supplied with predefined target labels. The model examines similarities, differences, and relationships to discover patterns or groups, with clustering being a common example. Predicting labeled targets is generally a supervised-learning task.

Related tags

Artificial IntelligenceClass 12Part B: Subject Specific SkillsUnit 2: Data Science MethodologyUnsupervised LearningClusteringUnlabelled DataPattern Recognition

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