Active Learning Strategy
Active learning is a machine learning strategy where the algorithm intelligently selects data points to be labeled by a human annotator. Instead of passively receiving labeled data, the model queries for labels on the most informative or uncertain data, aiming to achieve high accuracy with a minimal amount of labeled data. This is particularly useful when labeling data is expensive or time-consuming.
It's like a student asking the teacher specific questions about topics they find confusing, rather than studying everything equally.
Active learning significantly reduces the cost and effort of data labeling, accelerating model development in data-scarce or expensive domains.
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