h2o.saveGrid | R Documentation |
Returns a reference to the saved Grid.
h2o.saveGrid(
grid_directory,
grid_id,
save_params_references = FALSE,
export_cross_validation_predictions = FALSE
)
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. |
Returns an object that is a subclass of H2OGrid.
## 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)
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