View source: R/balanced_data.R
balanced.train.and.test | R Documentation |
Get a balanced test and train dataset
balanced.train.and.test(..., train.perc = 0.9, join.all = TRUE)
... |
vectors of index (could be numeric or logical) |
train.perc |
percentage of dataset to be training set |
join.all |
join all index in the end in two vectors (train and test vectors) |
train and test index vectors (two lists if 'join.all = FALSE', two vectors otherwise)
set1 <- seq(20) balanced.train.and.test(set1, train.perc = .9) #### set.seed(1985) set1 <- rbinom(20, prob = 3/20, size = 1) == 1 balanced.train.and.test(set1, train.perc = .9) #### set1 <- c(TRUE,TRUE,TRUE,TRUE,TRUE,TRUE,TRUE,TRUE,FALSE, TRUE,TRUE,TRUE,TRUE,TRUE,TRUE,TRUE,TRUE,TRUE,FALSE,TRUE) set2 <- !set1 balanced.train.and.test(set1, set2, train.perc = .9)
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