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

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Mon May 06, 2019 5:39 pm

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.

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

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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")
Attachments
mulset.zip
(86.85 KiB) Downloaded 1181 times
“We can not solve our problems with the same level of thinking that created them” A.E.
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