# NOT RUN {
library(h2o)
h2o.init()
h2o.no_progress()
f <- "http://h2o-public-test-data.s3.amazonaws.com/smalldata/iris/iris_wheader.csv"
iris <- h2o.importFile(f)
iris["class"] <- as.factor(iris["class"])
predictors <- c("sepal_len", "sepal_wid", "petal_len", "petal_wid")
splits <- h2o.splitFrame(iris, ratios = 0.8, seed = 1234)
train <- splits[[1]]
valid <- splits[[2]]
iris_km <- h2o.kmeans(x = predictors,
training_frame = train,
validation_frame = valid,
k = 10, estimate_k = TRUE,
standardize = FALSE, seed = 1234)
# }
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