data: An H2OFrame object containing the categorical columns.
destination_frame: A string indicating the destination key. If empty, this will be auto-generated by H2O.
factors: Factor columns (either indices or column names).
pairwise: Whether to create pairwise interactions between factors (otherwise create one higher-order interaction). Only applicable if there are 3 or more factors.
max_factors: Max. number of factor levels in pair-wise interaction terms (if enforced, one extra catch-all factor will be made)
min_occurrence: Min. occurrence threshold for factor levels in pair-wise interaction terms
Returns
Returns an H2OFrame object.
Examples
## Not run:library(h2o)h2o.init()# Create some random datamy_frame <- h2o.createFrame(rows =20, cols =5, seed =-12301283, randomize =TRUE, value =0, categorical_fraction =0.8, factors =10, real_range =1, integer_fraction =0.2, integer_range =10, binary_fraction =0, binary_ones_fraction =0.5, missing_fraction =0.2, response_factors =1)# Turn integer column into a categoricalmy_frame[,5]<- as.factor(my_frame[,5])head(my_frame,20)# Create pairwise interactionspairwise <- h2o.interaction(my_frame, factors = list(c(1,2), c("C2","C3","C4")), pairwise =TRUE, max_factors =10, min_occurrence =1)head(pairwise,20)h2o.levels(pairwise,2)# Create 5-th order interactionhigherorder <- h2o.interaction(my_frame, factors = c(1,2,3,4,5), pairwise =FALSE, max_factors =10000, min_occurrence =1)head(higherorder,20)# Limit the number of factors of the "categoricalized" integer column# to at most 3 factors, and only if they occur at least twicehead(my_frame[,5],20)trim_integer_levels <- h2o.interaction(my_frame, factors ="C5", pairwise =FALSE, max_factors =3, min_occurrence =2)head(trim_integer_levels,20)# Put all togethermy_frame <- h2o.cbind(my_frame, pairwise, higherorder, trim_integer_levels)my_frame
head(my_frame,20)summary(my_frame)## End(Not run)