if (FALSE) {
library(h2o)
h2o.init()
df <- h2o.createFrame(rows = 100,
cols = 5,
categorical_fraction = 0.6,
integer_fraction = 0,
binary_fraction = 0,
real_range = 100,
integer_range = 100,
missing_fraction = 0)
target_num_exemplars = 1000
rel_tol_num_exemplars = 0.5
encoding = "Eigen"
agg <- h2o.aggregator(training_frame = df,
target_num_exemplars = target_num_exemplars,
rel_tol_num_exemplars = rel_tol_num_exemplars,
categorical_encoding = encoding)
# Use the aggregated frame to create a new dataframe
new_df <- h2o.aggregated_frame(agg)
}
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