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. |
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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) # }