Graphical toolbox for clustering and classification of data frames.
It proposes a graphical interface to process clustering and classification methods on features
data-frames, and to view initial data as well as resulted cluster or classes. According to the
level of available labels, different approaches are proposed: unsupervised clustering,
semi-supervised clustering and supervised classification.
To assess the processed clusters or classes, the toolbox can import and show some supplementary
data formats: either profile/time series, or images.
These added information can help the expert to label clusters (clustering), or to constrain data
frame rows (semi-supervised clustering), using Constrained spectral embedding algorithm by
Wacquet et al. (2013) <doi:10.1016/j.patrec.2013.02.003> and the methodology provided by
Wacquet et al. (2013) <doi:10.1007/978-3-642-35638-4_21>.
| Version: |
0.91.6 |
| Depends: |
R (≥ 3.0.0), tcltk, tcltk2, tkrplot |
| Imports: |
class, cluster, conclust, corrplot, e1071, factoextra, FactoMineR, ggplot2, grid, jpeg, knitr, MASS, mclust, mda, mmand, nnet, png, randomForest, reshape, rlang, SearchTrees, sp, stats, stringi, stringr, tools |
| Published: |
2024-02-27 |
| DOI: |
10.32614/CRAN.package.RclusTool |
| Author: |
Guillaume Wacquet [aut],
Pierre-Alexandre Hebert [aut, cre],
Emilie Poisson [aut],
Pierre Talon [aut] |
| Maintainer: |
Pierre-Alexandre Hebert <hebert at univ-littoral.fr> |
| License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| URL: |
mawenzi.univ-littoral.fr/RclusTool |
| NeedsCompilation: |
no |
| SystemRequirements: |
XQuartz (on OSX) |
| Citation: |
RclusTool citation info |
| CRAN checks: |
RclusTool results |