h2o.interaction: Categorical Interaction Feature Creation in H2O

In h2o: R Interface for the 'H2O' Scalable Machine Learning Platform

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

## Not run: 
library(h2o)
h2o.init()

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

# Create pairwise interactions
pairwise <- 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 interaction
higherorder <- 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 twice
head(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 together
my_frame <- h2o.cbind(my_frame, pairwise, higherorder, trim_integer_levels)
my_frame
head(my_frame, 20)
summary(my_frame)

## End(Not run)

h2o documentation built on May 29, 2024, 4:26 a.m.