NIMAA: Nominal Data Mining Analysis

Functions for nominal data mining based on bipartite graphs, which build a pipeline for analysis and missing values imputation. Methods are mainly from the paper: Jafari, Mohieddin, et al. (2021) <doi:10.1101/2021.03.18.436040>, some new ones are also included.

Version: 0.2.1
Depends: R (≥ 3.5.0)
Imports: plotly, tidyr, bipartite, crayon, dplyr, ggplot2, igraph, purrr, skimr, bnstruct, RColorBrewer, fpc, mice, missMDA, networkD3, scales, softImpute, tibble, tidytext, visNetwork, stats
Suggests: knitr, utils, rmarkdown, htmltools, testthat (≥ 3.0.0)
Published: 2022-04-11
DOI: 10.32614/CRAN.package.NIMAA
Author: Mohieddin Jafari [aut, cre], Cheng Chen [aut]
Maintainer: Mohieddin Jafari <mohieddin.jafari at>
License: GPL (≥ 3)
NeedsCompilation: no
Materials: README NEWS
In views: MissingData
CRAN checks: NIMAA results


Reference manual: NIMAA.pdf
Vignettes: NIMAA-vignette


Package source: NIMAA_0.2.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): NIMAA_0.2.1.tgz, r-oldrel (arm64): NIMAA_0.2.1.tgz, r-release (x86_64): NIMAA_0.2.1.tgz, r-oldrel (x86_64): NIMAA_0.2.1.tgz
Old sources: NIMAA archive


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