Answer / Anil Singh Dariyal

Candidate sampling (or active learning) is a technique used in machine learning where the algorithm selects specific data points from a larger dataset to label or annotate based on their uncertainty or relevance. This helps the algorithm improve its performance by focusing on the most informative samples.

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