h2o.ddply: Split H2O Dataset, Apply Function, and Return Results

In h2o: R Interface for the 'H2O' Scalable Machine Learning Platform

Split H2O Dataset, Apply Function, and Return Results

Description

For each subset of an H2O data set, apply a user-specified function, then combine the results. This is an experimental feature based on plyr::ddply.

Usage

h2o.ddply(X, .variables, FUN, ..., .progress = "none")

Arguments

X	An H2OFrame object to be processed.
.variables	Variables to split X by, either the indices or names of a set of columns.
FUN	Function to apply to each subset grouping.
...	Additional arguments passed on to FUN.
.progress	Name of the progress bar to use. #TODO: (Currently unimplemented)

Value

Returns an H2OFrame object containing the results from the split/apply operation, arranged

Examples

## Not run: 
library(h2o)
h2o.init()

# Import iris dataset to H2O
iris_hf <- as.h2o(iris)
# Add function taking mean of Sepal.Length column
fun <- function(df) { sum(df[, 1], na.rm = TRUE) / nrow(df) }
# Apply function to groups by flower specie
# uses h2o's ddply, since iris_hf is an H2OFrame object
res <- h2o.ddply(iris_hf, "Species", fun)
head(res)

## End(Not run)

h2o documentation built on May 29, 2024, 4:26 a.m.