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 |