if (FALSE) {
# Import default Iris dataset as H2O frame
data <- as.h2o(iris)
# Train a very simple GBM model
features <- c("Sepal.Length", "Sepal.Length", "Sepal.Width", "Petal.Length", "Petal.Width")
original_model <- h2o.gbm(x = features, y = "Species", training_frame = data)
# Download the trained GBM model as MOJO (temporary directory used in this example)
mojo_original_path <- h2o.save_mojo(original_model, path = tempdir())
# Import the MOJO and obtain a Generic model
mojo_model <- h2o.import_mojo(mojo_original_path)
# Perform scoring with the generic model
predictions <- h2o.predict(mojo_model, data)
}
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