Save an H2OModel to disk. (Note that ensemble binary models can be saved.)
h2o.saveModel( object, path = "", force = FALSE, export_cross_validation_predictions = FALSE )
| object | an H2OModel object. |
|---|---|
| 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. |
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)
# }