`createDataPartition`

while `createResample`

creates one or
more bootstrap samples. `createFolds`

splits the data into
`k`

groups.```
createDataPartition(y,
times = 1,
p = 0.5,
list = TRUE,
groups = min(5, length(y)))
createResample(y, times = 10, list = TRUE)
createFolds(y, k = 10, list = TRUE, returnTrain = FALSE)
createMultiFolds(y, k = 10, times = 5)
```

y

a vector of outcomes

times

the number of partitions to create

p

the percentage of data that goes to training

list

logical - should the results be in a list (

`TRUE`

) or a matrix
with the number of rows equal to `floor(p * length(y))`

and `times`

columns.groups

for numeric

`y`

, the number of breaks in the quantiles
(see below)k

an integer for the number of folds.

returnTrain

a logical. When true, the values returned are the
sample positions corresponding to the data used during
training. This argument only works in conjunction with

`list = TRUE`

- A list or matrix of row position integers corresponding to the training data

For other data splitting, the random sampling is done within the
levels of `y`

when `y`

is a factor in an attempt to balance
the class distributions within the splits. For numeric `y`

, the
sample is split into `groups`

sections based
on quantiles and sampling is done within these subgroups. Also, for
very small class sizes (<= 3)="" the="" classes="" may="" not="" show="" up="" in="" both="" training="" and="" test="" data<="" p="">

For multiple k-fold cross-validation, completely independent folds are created.
The names of the list objects will denote the fold membership using the pattern
"Foldi.Repj" meaning the ith section (of k) of the jth cross-validation set
(of `times`

). Note that this function calls `createFolds`

with
`list = TRUE`

and `returnTrain = TRUE`

.

data(oil) createDataPartition(oilType, 2) x <- rgamma(50, 3, .5) inA <- createDataPartition(x, list = FALSE) plot(density(x[inA])) rug(x[inA]) points(density(x[-inA]), type = "l", col = 4) rug(x[-inA], col = 4) createResample(oilType, 2) createFolds(oilType, 10) createFolds(oilType, 5, FALSE) createFolds(rnorm(21))