h2o: h2o.saveGrid – R documentation

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h2o

h2o.saveGrid

Saves an existing Grid of models into a given folder.

Description

Returns a reference to the saved Grid.

Usage

h2o.saveGrid(
  grid_directory,
  grid_id,
  save_params_references = FALSE,
  export_cross_validation_predictions = FALSE
)

Arguments

`grid_directory`	A character string containing the path to the folder for the grid to be saved to.
`grid_id`	A chracter string with identification of the grid to be saved.
`save_params_references`	A logical indicating if objects referenced by grid parameters (e.g. training frame, calibration frame) should also be saved.
`export_cross_validation_predictions`	A logical indicating whether exported model artifacts should also include CV holdout Frame predictions.

Value

Returns an object that is a subclass of H2OGrid.

Examples

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

iris <- as.h2o(iris)

ntrees_opts = c(1, 5)
learn_rate_opts = c(0.1, 0.01)
size_of_hyper_space = length(ntrees_opts) * length(learn_rate_opts)

hyper_parameters = list(ntrees = ntrees_opts, learn_rate = learn_rate_opts)
# Tempdir is chosen arbitrarily. May be any valid folder on an H2O-supported filesystem.
baseline_grid <- h2o.grid(algorithm = "gbm", 
                         grid_id = "gbm_grid_test", 
                         x = 1:4, 
                         y = 5, 
                         training_frame = iris,
                         hyper_params = hyper_parameters)

grid_path <- h2o.saveGrid(grid_directory = tempdir(), grid_id = baseline_grid@grid_id)
# Remove everything from the cluster or restart it
h2o.removeAll()
grid <- h2o.loadGrid(grid_path)

## 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