In which scenario is unsupervised learning least suitable: predicting house prices based on features, grouping customers into segments, or classifying emails as spam or not spam?
- Classifying emails as spam or not spam
- Grouping customers into segments
- Predicting house prices based on features
- Unsupervised learning is suitable for all scenarios
Unsupervised learning is least suitable for classifying emails as spam or not spam. This is because unsupervised learning doesn't have labeled data to distinguish between spam and non-spam emails. It is more applicable to clustering or grouping data when you don't have clear labels, such as grouping customers into segments.
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