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AutoML in h2o

A very convenient functionality of h2o is automatic machine learning (AutoML). The h2o library and seeds_train_data have already been loaded for you and the following code has been run:

h2o.init()
seeds_train_data_hf <- as.h2o(seeds_train_data)

y <- "seed_type"
x <- setdiff(colnames(seeds_train_data_hf), y)

seeds_train_data_hf[, y] <- as.factor(seeds_train_data_hf[, y])

sframe <- h2o.splitFrame(seeds_train_data_hf, seed = 42)
train <- sframe[[1]]
valid <- sframe[[2]]

This exercise is part of the course

Hyperparameter Tuning in R

View Course

Hands-on interactive exercise

Have a go at this exercise by completing this sample code.

# Run automatic machine learning
automl_model <- ___(x = x, 
                    y = y,
                    training_frame = train,
                    ___ = 10,
                    seed = 42)
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