if (FALSE) {
library(h2o)
h2o.init()
f <- "https://s3.amazonaws.com/h2o-public-test-data/smalldata/prostate/prostate_complete.csv.zip"
pros <- h2o.importFile(f)
response <- "GLEASON"
predictors <- c("ID", "AGE", "CAPSULE", "DCAPS", "PSA", "VOL", "DPROS")
aml <- h2o.automl(x = predictors, y = response, training_frame = pros, max_runtime_secs = 60)
h2o.varimp(aml, top_n = 20) # get variable importance matrix for the top 20 models
h2o.varimp(aml@leader) # get variable importance for the leader model
}
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