Package: cleanerR
Type: Package
Title: How to Handle your Missing Data
Version: 0.1.1
Author: Rafael Silva Pereira
Maintainer: Rafael Silva Pereira <r.s.p.models@gmail.com>
Description: How to deal with missing data?Based on the concept of almost functional dependencies, a method is proposed to fill missing data, as well as help you see what data is missing.
    The user can specify a measure of error and how many combinations he wish to test the dependencies against, the closer to the length of the dataset, the more precise.
    But the higher the number, the more time it will take for the process to finish.
    If the program cannot predict with the accuracy determined by the user it shall not fill the data, the user then can choose to increase the error or deal with the data another way.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0.9000
Imports: plyr, data.table
Suggests: knitr, rmarkdown, testthat
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-02-04 20:20:51 UTC; rpereira
Repository: CRAN
Date/Publication: 2019-02-10 14:03:11 UTC
