# h2o.splitFrame

##### Split an H2O Data Set

Split an existing H2O data set according to user-specified ratios. The number of subsets is always 1 more than the number of given ratios. Note that this does not give an exact split. H2O is designed to be efficient on big data using a probabilistic splitting method rather than an exact split. For example, when specifying a split of 0.75/0.25, H2O will produce a test/train split with an expected value of 0.75/0.25 rather than exactly 0.75/0.25. On small datasets, the sizes of the resulting splits will deviate from the expected value more than on big data, where they will be very close to exact.

##### Usage

`h2o.splitFrame(data, ratios = 0.75, destination_frames, seed = -1)`

##### Arguments

- data
An H2OFrame object representing the dataste to split.

- ratios
A numeric value or array indicating the ratio of total rows contained in each split. Must total up to less than 1.

- destination_frames
An array of frame IDs equal to the number of ratios specified plus one.

- seed
Random seed.

##### Value

Returns a list of split H2OFrame's

##### Examples

```
# NOT RUN {
library(h2o)
h2o.init()
iris_hf <- as.h2o(iris)
iris_split <- h2o.splitFrame(iris_hf, ratios = c(0.2, 0.5))
head(iris_split[[1]])
summary(iris_split[[1]])
# }
```

*Documentation reproduced from package h2o, version 3.22.1.1, License: Apache License (== 2.0)*