h2o (version 3.10.3.6)

h2o.splitFrame: Split an H2O Data Set

Description

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.

Examples

Run this code
library(h2o)
h2o.init()
irisPath = system.file("extdata", "iris.csv", package = "h2o")
iris.hex = h2o.importFile(path = irisPath)
iris.split = h2o.splitFrame(iris.hex, ratios = c(0.2, 0.5))
head(iris.split[[1]])
summary(iris.split[[1]])

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