if (FALSE) {
library(h2o)
h2o.init()
iris_hf <- as.h2o(iris)
h2o.train_segments(algorithm = "gbm",
segment_columns = "Species", segment_models_id="models_by_species",
x = c(1:3), y = 4, training_frame = iris_hf, ntrees = 5, max_depth = 4)
models <- h2o.get_segment_models("models_by_species")
as.data.frame(models)
}
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