H2O AutoML models require a special storage process that saves / loads the recipe used to recreate a model to / from a directory that the user defines.

save_h2o_model(object, path, overwrite = FALSE)

load_h2o_model(path)

Arguments

object

A fitted model object

path

A directory to store the H2O AutoML model files

overwrite

Whether or not to allow overwriting a H2O AutoML model's directory. Default: FALSE.

Value

  • save_h2o_model(): No return value, called for side effects (composes a directory of model files)

  • load_h2o_model(): No return value, called for side effects (reads a directory of model files)

Examples

if (FALSE) { library(tidymodels) library(tidyverse) library(timetk) library(modeltime.h2o) h2o.init() model_fit <- automl_reg(mode = 'regression') %>% set_engine( engine = 'h2o', max_runtime_secs = 30, max_runtime_secs_per_model = 30, project_name = 'project_01', nfolds = 5, max_models = 1000, exclude_algos = c("DeepLearning"), seed = 786 ) %>% fit(value ~ date + id, m750) # Saves the related files needed to recreate the model model_fit %>% save_h2o_model(path = "/dir_h2o_automl_model/") # Loads the model load_h2o_model(path = "/dir_h2o_automl_model/") # Shutdown H2O when Finished. # Make sure to save any work before. h2o.shutdown(prompt = FALSE) }