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Here explains the function numpy.random.choice. However, I am confused about the third parameter replace. What is it? And in which case will it be useful? Thanks!
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You can use it when you want sample some elements from a list, and meanwhile you want the elements no repeat, then you can set the "replace=False". eg.
Sampling with replacement can be defined as random sampling that allows sampling units to occur more than once. Sampling with replacement consists of. A sampling unit (like a glass bead or a row of data) being randomly drawn from a population (like a jar of beads or a dataset).
The NumPy random choice function randomly selected 5 numbers from the input array, which contains the numbers from 0 to 99. The output is basically a random sample of the numbers from 0 to 99.
random. choice() in Python. With the help of choice() method, we can get the random samples of one dimensional array and return the random samples of numpy array.
It controls whether the sample is returned to the sample pool. If you want only unique samples then this should be false.
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