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>.
Package details |
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Author | Guillaume Wacquet [aut], Pierre-Alexandre Hebert [aut, cre], Emilie Poisson [aut], Pierre Talon [aut] |
Maintainer | Pierre-Alexandre Hebert <hebert@univ-littoral.fr> |
License | GPL (>= 2) |
Version | 0.91.6 |
URL | mawenzi.univ-littoral.fr/RclusTool |
Package repository | View on CRAN |
Installation |
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