one_hot: One Hot Encoding of data.table columns

In Nth-iteration-labs/contextual: Simulation and Analysis of Contextual Multi-Armed Bandit Policies

Description

One-Hot-Encode unordered factor columns of a data.table mltools. From ben519's "mltools" package.

Usage

one_hot(
  dt,
  cols = "auto",
  sparsifyNAs = FALSE,
  naCols = FALSE,
  dropCols = TRUE,
  dropUnusedLevels = FALSE
)

Arguments

dt	A data.table
cols	Which column(s) should be one-hot-encoded? DEFAULT = "auto" encodes all unordered factor columns.
sparsifyNAs	Should NAs be converted to 0s?
naCols	Should columns be generated to indicate the present of NAs? Will only apply to factor columns with at least one NA
dropCols	Should the resulting data.table exclude the original columns which are one-hot-encoded?
dropUnusedLevels	Should columns of all 0s be generated for unused factor levels?

Details

One-hot-encoding converts an unordered categorical vector (i.e. a factor) to multiple binarized vectors where each binary vector of 1s and 0s indicates the presence of a class (i.e. level) of the of the original vector.

Examples

library(data.table)

dt <- data.table(
  ID = 1:4,
  color = factor(c("red", NA, "blue", "blue"), levels=c("blue", "green", "red"))
)

one_hot(dt)
one_hot(dt, sparsifyNAs=TRUE)
one_hot(dt, naCols=TRUE)
one_hot(dt, dropCols=FALSE)
one_hot(dt, dropUnusedLevels=TRUE)

Nth-iteration-labs/contextual documentation built on July 28, 2020, 1:13 p.m.