Save an H2OModel to disk. (Note that ensemble binary models can be saved.)
h2o.saveModel( object, path = "", force = FALSE, export_cross_validation_predictions = FALSE, filename = "" )
object | an H2OModel object. |
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path | string indicating the directory the model will be written to. |
force | logical, indicates how to deal with files that already exist. |
export_cross_validation_predictions | logical, indicates whether the exported model artifacts should also include CV Holdout Frame predictions. Default is not to export the predictions. |
filename | string indicating the file name. |
In the case of existing files force = TRUE
will overwrite the file.
Otherwise, the operation will fail.
The owner of the file saved is the user by which H2O cluster was executed.
h2o.loadModel
for loading a model to H2O from disk
# NOT RUN { # library(h2o) # h2o.init() # prostate <- h2o.importFile(path = paste("https://raw.github.com", # "h2oai/h2o-2/master/smalldata/logreg/prostate.csv", sep = "/")) # prostate_glm <- h2o.glm(y = "CAPSULE", x = c("AGE", "RACE", "PSA", "DCAPS"), # training_frame = prostate, family = "binomial", alpha = 0.5) # h2o.saveModel(object = prostate_glm, path = "/Users/UserName/Desktop", force = TRUE) # }