h2o.which_max(x, na.rm = TRUE, axis = 0)

which.max.H2OFrame(x, na.rm = TRUE, axis = 0)

which.min.H2OFrame(x, na.rm = TRUE, axis = 0)

## Not run: 
library(h2o)
h2o.init()

f <- "https://s3.amazonaws.com/h2o-public-test-data/smalldata/chicago/chicagoCensus.csv"
census <- h2o.importFile(f)
census[, 1] <- as.factor(census[, 1])
dl_model <- h2o.deeplearning(x = c(1:3), y = 4, hidden = c(17, 191), 
                            epochs = 1, training_frame = census, 
                            balance_classes = FALSE,
                            export_weights_and_biases = TRUE)
h2o.which_max(census["PER CAPITA INCOME "], na.rm = FALSE, axis = 0)

## End(Not run)