Exploratory data analysis and manipulation functions for multi-label data sets along with an interactive Shiny application to ease their use.
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")
Use devtools::build
from devtools
to build the package:
devtools::build(args = "--compact-vignettes=gs+qpdf")
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.
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}
}