Active learning is a form of supervised learning that is suitable for situations where data are abundant, yet the class labels are scarce or expensive to maintain and where the learning algorithm can query a person for labels.
What does supervised learning using examples mean?
- Predicting housing values is a real-world example of supervised learning issues.
- We must first gather information about the homes, such as their dimensions, number of rooms, characteristics, and whether or not they have gardens.
- The cost of these dwellings, or the labels that relate to them, must then be known. A subset of machine learning and artificial intelligence is supervised learning, commonly referred to as supervised machine learning.
- It is distinguished by the way it trains computers to properly categorize data or predict outcomes using labeled datasets.
- For issues where the data is in the form of labelled examples, where each data point has characteristics and a corresponding label, supervised learning is a machine learning paradigm.
To learn more about supervised learning refer to:
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