Awesome

mldr

Exploratory data analysis and manipulation functions for multi-label data sets along with an interactive Shiny application to ease their use.

Installation

Use install.packages to install mldr and its dependencies:

install.packages("mldr")

Alternatively, you can install it via install_github from the devtools package.

devtools::install_github("fcharte/mldr")

Building from source

Use devtools::build from devtools to build the package:

devtools::build(args = "--compact-vignettes=gs+qpdf")

Usage and examples

This package provides a web GUI able to load, visualize and manipulate multi-label data sets. You can launch it using the R console:

library(mldr)
mldrGUI()

There are several functions available as well, so that you can use mldr in an R script. For example, to explore some data sets:

library(mldr)

# Data sets birds, emotions and genbase are
# provided within the package
print(emotions)
summary(genbase)
plot(birds)

mldr enables you to create new multi-label data sets via the mldr_from_dataframe function, and export them to the standard ARFF format using write_arff:

library(mldr)

df <- data.frame(matrix(rnorm(1000), ncol = 10))
df$Label1 <- c(sample(c(0,1), 100, replace = TRUE))
df$Label2 <- c(sample(c(0,1), 100, replace = TRUE))
mymldr <- mldr_from_dataframe(df, labelIndices = c(11, 12), name = "testMLDR")

# Writes .arff and .xml files for a multi-label dataset
write_arff(mymldr, "my_new_mldr")

For more examples and detailed explanation on available functions, please refer to the documentation.

Citation

Please, cite mldr as follows:

@Article{charte-charte:2015,
  author       = {Francisco Charte and David Charte}, 
  title        = {Working with Multilabel Datasets in {R}: The mldr Package}, 
  journal      = {The R Journal},
  year         = 2015,
  volume       = 7,
  number       = 2,
  pages        = {149--162},
  month        = dec,
  url          = {https://journal.r-project.org/archive/2015-2/charte-charte.pdf}
}