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Sep 13, 2021 · Artificial Intelligence
Active Learning: Concepts, Workflow, Strategies, and Evaluation Metrics
Active learning addresses the high cost of labeling data by iteratively selecting the most informative unlabeled samples for annotation, thereby reducing labeling effort while achieving target model performance, and the article explains its fundamentals, relationship to supervised and semi‑supervised learning, common selection strategies, hybrid methods, and evaluation metrics.
Labeling Cost ReductionQuery by CommitteeUncertainty Sampling
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