sparsify: Sparsify

In ben519/mltools: Machine Learning Tools

Description

Convert a data.table object into a sparse matrix (with the same number of rows).

Usage

sparsify(
  dt,
  sparsifyNAs = FALSE,
  naCols = "none",
  sparsifyCols = NULL,
  memEfficient = FALSE
)

Arguments

dt	A data.table object
sparsifyNAs	Should NAs be converted to 0s and sparsified?
naCols	"none" Don't generate columns to identify NA values "identify" For each column of dt with an NA value, generate a column in the sparse matrix with 1s indicating NAs. Columns will be named like "color_NA" "efficient" For each column of dt with an NA value, generate a column in the sparse matrix with 1s indicating either NAs or Non NAs - whichever is more memory efficient. Columns will be named like "color_NA" or "color_NotNA"
sparsifyCols	What columns to use. Use this to exclude columns of dt from being sparsified without having to build a column-subsetted copy of dt to input into sparsify(...). Default = NULL means use all columns of dt.
memEfficient	Default = FALSE. Set this to TRUE for a slower but more memory efficient process

Details

Converts a data.table object to a sparse matrix (class "dgCMatrix"). Requires the Matrix package. All sparsified data is assumed to take on the value 0/FALSE

### Data Type | Description & NA handling

numeric | If sparsifyNAs = FALSE, only 0s will be sparsified If sparsifyNAs = TRUE, 0s and NAs will be sparsified

factor (unordered) | Each level will generate a sparsified binary column Column names are feature_level, e.g. "color_red", "color_blue"

factor (ordered) | Levels are converted to numeric, 1 - NLevels If sparsifyNAs = FALSE, NAs will remain as NAs If sparsifyNAs = TRUE, NAs will be sparsified

logical | TRUE and FALSE values will be converted to 1s and 0s If sparsifyNAs = FALSE, only FALSEs will be sparsified If sparsifyNAs = TRUE, FALSEs and NAs will be sparsified

Examples

library(data.table)
library(Matrix)

dt <- data.table(
  intCol=c(1L, NA_integer_, 3L, 0L),
  realCol=c(NA, 2, NA, NA),
  logCol=c(TRUE, FALSE, TRUE, FALSE),
  ofCol=factor(c("a", "b", NA, "b"), levels=c("a", "b", "c"), ordered=TRUE),
  ufCol=factor(c("a", NA, "c", "b"), ordered=FALSE)
)

sparsify(dt)
sparsify(dt, sparsifyNAs=TRUE)
sparsify(dt[, list(realCol)], naCols="identify")
sparsify(dt[, list(realCol)], naCols="efficient")

ben519/mltools documentation built on Sept. 22, 2021, 4:30 p.m.