h2o.mojo_predict_csv: H2O Prediction from R without having H2O running
In h2o: R Interface for the 'H2O' Scalable Machine Learning Platform

h2o.mojo_predict_csv

R Documentation

H2O Prediction from R without having H2O running

Description

Provides the method h2o.mojo_predict_csv with which you can predict a MOJO model from R.

Usage

h2o.mojo_predict_csv(
  input_csv_path,
  mojo_zip_path,
  output_csv_path = NULL,
  genmodel_jar_path = NULL,
  classpath = NULL,
  java_options = NULL,
  verbose = F,
  setInvNumNA = F
)

Arguments

`input_csv_path`	Path to input CSV file.
`mojo_zip_path`	Path to MOJO zip downloaded from H2O.
`output_csv_path`	Optional, path to the output CSV file with computed predictions. If NULL (default), then predictions will be saved as prediction.csv in the same folder as the MOJO zip.
`genmodel_jar_path`	Optional, path to genmodel jar file. If NULL (default) then the h2o-genmodel.jar in the same folder as the MOJO zip will be used.
`classpath`	Optional, specifies custom user defined classpath which will be used when scoring. If NULL (default) then the default classpath for this MOJO model will be used.
`java_options`	Optional, custom user defined options for Java. By default '-Xmx4g -XX:ReservedCodeCacheSize=256m' is used.
`verbose`	Optional, if TRUE, then additional debug information will be printed. FALSE by default.
`setInvNumNA`	Optional, if TRUE, then then for an string that cannot be parsed into a number an N/A value will be produced, if false the command will fail. FALSE by default.