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 helsinki.fi> BugReports: https://github.com/jafarilab/NIMAA/issues License: GPL (≥ 3) URL: https://github.com/jafarilab/NIMAA NeedsCompilation: no Materials: README NEWS In views: MissingData CRAN checks: NIMAA results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=NIMAA to link to this page.
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