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
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)