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[R-Package] mulset - generate dataset intersections in sparse data

Posted: Mon May 06, 2019 5:39 pm
by LogIN
Description

If you have missing values in your data, but you dont want to impute those values or mess with them in any other artificial way,
you can use mulset and generate multiple datasets of those data that you can use latter on in autoML or some other analysis.

Image

Download links
  • https://cran.r-project.org/web/packages/mulset/index.html
  • https://github.com/LogIN-/mulset
Installation

Code: Select all

install.packages("devtools")
devtools::install_github("LogIN-/mulset", subdir = 'R-package')
Usage Example

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library("mulset")
## Using provided demo data
data(mulsetDemo)
resamples <- mulset(mulsetDemo, exclude = c("outcome", "age", "gender"), 250)

## or from CSV file
## mulsetDemo <-fread("./data/mulsetDemo.csv", header = T, sep = ',', stringsAsFactors = FALSE, data.table = FALSE)
## exclude <- c("come_column")
## resamples <- mulset(mulsetDemo, exclude = exclude, include = c("samples_count", "datapoints"), maxIntersections = 250, hashMethod = "sha1")