h2o (version 3.8.3.3)

h2o.interaction: Categorical Interaction Feature Creation in H2O

Description

Creates a data frame in H2O with n-th order interaction features between categorical columns, as specified by the user.

Usage

h2o.interaction(data, destination_frame, factors, pairwise, max_factors, min_occurrence)

Arguments

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

Value

Returns an H2OFrame object.

Examples

library(h2o)
h2o.init()

# Create some random data
myframe = 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 categorical
myframe[,5] <- as.factor(myframe[,5])
head(myframe, 20)

# Create pairwise interactions
pairwise <- h2o.interaction(myframe, destination_frame = 'pairwise',
                            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 interaction
higherorder <- h2o.interaction(myframe, destination_frame = 'higherorder', 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 twice
head(myframe[,5], 20)
trim_integer_levels <- h2o.interaction(myframe, destination_frame = 'trim_integers', factors = "C5",
                                       pairwise = FALSE, max_factors = 3, min_occurrence = 2)
head(trim_integer_levels, 20)

# Put all together
myframe <- h2o.cbind(myframe, pairwise, higherorder, trim_integer_levels)
myframe
head(myframe,20)
summary(myframe)