data_sample: Data sampling abstractions

In daltoolbox: Leveraging Experiment Lines to Data Analytics

Data sampling abstractions

Description

Base class for sampling strategies that provide train/test splitting and k‑fold partitioning. Two standard implementations are sample_random() and sample_stratified().

Usage

data_sample()

Value

returns an object of class data_sample

Examples

#using random sampling
sample <- sample_random()
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)

daltoolbox documentation built on Nov. 5, 2025, 7:09 p.m.