h2o: h2o.download_mojo – R documentation

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h2o

h2o.download_mojo

Download the model in MOJO format.

Description

Download the model in MOJO format.

Usage

h2o.download_mojo(
  model,
  path = getwd(),
  get_genmodel_jar = FALSE,
  genmodel_name = "",
  genmodel_path = ""
)

Arguments

`model`	An H2OModel
`path`	The path where MOJO file should be saved. Saved to current directory by default.
`get_genmodel_jar`	If TRUE, then also download h2o-genmodel.jar and store it in either in the same folder
`genmodel_name`	Custom name of genmodel jar.
`genmodel_path`	Path to store h2o-genmodel.jar. If left blank and “get_genmodel_jar“ is TRUE, then the h2o-genmodel.jar

Value

Name of the MOJO file written to the path.

Examples

## Not run: 
library(h2o)
h <- h2o.init()
fr <- as.h2o(iris)
my_model <- h2o.gbm(x = 1:4, y = 5, training_frame = fr)
h2o.download_mojo(my_model)  # save to the current working directory

## End(Not run)

h2o

R Interface for the 'H2O' Scalable Machine Learning Platform

v3.32.1.2

Apache License (== 2.0)

Authors

Erin LeDell [aut, cre], Navdeep Gill [aut], Spencer Aiello [aut], Anqi Fu [aut], Arno Candel [aut], Cliff Click [aut], Tom Kraljevic [aut], Tomas Nykodym [aut], Patrick Aboyoun [aut], Michal Kurka [aut], Michal Malohlava [aut], Ludi Rehak [ctb], Eric Eckstrand [ctb], Brandon Hill [ctb], Sebastian Vidrio [ctb], Surekha Jadhawani [ctb], Amy Wang [ctb], Raymond Peck [ctb], Wendy Wong [ctb], Jan Gorecki [ctb], Matt Dowle [ctb], Yuan Tang [ctb], Lauren DiPerna [ctb], Tomas Fryda [ctb], H2O.ai [cph, fnd]

Initial release

2021-04-29