The goal of goldrake is to provide an environment to create gold-standard databases for a classification task.
You can install the development version from GitHub with the following procedure:
# install.packages("devtools")
devtools::install_github("CorradoLanera/goldrake")The intended is divided in multiple step.
library(goldrake)
mtcars_gr <- goldrake(mtcars) %>%
set_gold_classes(c("good", "bad", "so and so")) %>%
balance_groups_by(vs, am) %>%
# max_sample_each_group(5) %>% # DOES IT WORTH TO BE IMPLEMENTED??
add_reviewer("Corrado", "Lanera")
#> <U+2714> Classes have been added.
#> <U+2714> New classes: 'good', 'bad', 'so and so'.
#> <U+2714> Balancing variables setted
#> <U+2714> New balancing variables: 'vs', 'am'
#> <U+2714> Reviewer 'Corrado, Lanera' added.
mtcars_gr
#> goldrake classification object
#>
#> <U+2714> 32 cases and 11 variables (balanced by vs, am)
#> <U+2714> Classes: good, bad, so and so.
#>
#> <U+2714> Data classified: 0 (by everyone) -- 0 (by someone)
#> <U+25CF> Data left to classify: 32 (by someone) -- 32 (by everyone)
#>
#> <U+2714> Reviewers: Corrado, Lanera.You can add reviewer in any moment (even if the previous ones have already started to classify objects).
mtcars_gr %>%
add_reviewer("Daniele", "Bottigliengo") # it asks for a password
## if it is not the first time
# mtcars_gr <- read_goldrake("mtcars_gr.goldrake")
# start the interactive classification session
mtcars_gr %>%
classify_by("Corrado") # it asks for reviewer's password
At the end of the session, if the stored goldrake was updated by other reviewer(s), the information will be merged together.
# load_goldrake("mtcars_gr.goldrake") # if it is not already loaded
classified_mtcars <- mtcars_gr %>%
extract_classified_tbl()
is.data.frame(classified_mtcars)
Please note that the goldrake project is released with a Contributor
Code of Conduct. By contributing to this
project, you agree to abide by its terms.