= Reservoir sampling
{wiki=Reservoir_sampling}
Reservoir sampling is a family of randomized algorithms used to sample a fixed number of elements from a population of unknown size. It's particularly useful when the total number of items is large or potentially infinite, and it allows you to select a representative sample without needing to know the size of the entire dataset. \#\#\# Key Characteristics of Reservoir Sampling: 1. **Stream Processing**: It allows for sampling elements from a stream of data where the total number of elements is not known in advance.
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