问题
If I have a large dataset in R, how can I take random sample of the data taking into consideration the distribution of the original data, particularly if the data are skewed and only 1% belong to a minor class and I want to take a biased sample of the data?
回答1:
The sample(x, n, replace = FALSE, prob = NULL) function takes a sample from a vector x of size n. This sample can be with or without replacement, and the probabilities of selecting each element to the sample can be either the same for each element, or a vector informed by the user.
If you want to take a sample of same probabilities for each element with 50 cases, all you have to do is
n <- 50
smpl <- df[sample(nrow(df), 50),]
However, if you want to give different probabilities of being selected for the elements, let's say, elements that sex is M has probability 0.25, while those whose sex is F has prob 0.75, you should do
n <- 50
prb <- ifelse(sex=="M",0.25,0.75)
smpl <- df[sample(nrow(df), 50, prob = prb),]
来源：https://stackoverflow.com/questions/10240991/taking-a-disproportionate-sample-from-a-dataset-in-r