View source: R/trans_sample_strat.R
sample_stratified | R Documentation |
The sample_stratified function in R is used to generate a stratified random sample from a given dataset. Stratified sampling is a statistical method that is used when the population is divided into non-overlapping subgroups or strata, and a sample is selected from each stratum to represent the entire population. In stratified sampling, the sample is selected in such a way that it is representative of the entire population and the variability within each stratum is minimized.
sample_stratified(attribute)
attribute |
attribute target to model building |
obj
#using stratified sampling
sample <- sample_stratified("Species")
tt <- train_test(sample, iris)
# distribution of train
table(tt$train$Species)
# preparing dataset into four folds
folds <- k_fold(sample, iris, 4)
# distribution of folds
tbl <- NULL
for (f in folds) {
tbl <- rbind(tbl, table(f$Species))
}
head(tbl)
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