Sampling with/without replacement

Sampling with/without replacement                       Machine Learning

noun phrase

Definition: Sampling with replacement means selected items are returned to the population before the next draw (so the same item may be selected multiple times); sampling without replacement means selected items are not returned and cannot be selected again in the same sample [IBM].

Example in context:It begins with bootstrapped sampling, where multiple subsets of the training data are created through random sampling with replacement. [ Pushkaran, Arabi 2024]

“After preprocessing, we split the data into training (70%) and testing (30%) sets via random sampling without replacement.” [Santos, Shinjo 2025]

Related terms: bootstrap sampling (with replacement), simple random sampling (often without replacement), resampling

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