The RandomSample function takes a data set and uses a specified sampling method to output one or more random samples. Each sample has exactly the number of rows specified.
The RandomSample function is useful for creating test sets, training sets, and initial centers for clustering algorithms.
In addition to the default basic sampling, in which each input table row has a probability of being selected that is proportional to its weight, this function provides two alternate methods, KMeans++ and KMeans||, which are designed for creating a set of initial seeds for the function KMeans (ML Engine).