Graphical Toolbox for Clustering and Classification of Data Frames

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) and the methodology provided by Wacquet et al. (2013) .


Reference manual

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0.91.3 by Pierre-Alexandre Hebert, a year ago

Browse source code at

Authors: Guillaume Wacquet [aut] , Pierre-Alexandre Hebert [aut, cre] , Emilie Poisson [aut] , Pierre Talon [aut]

Documentation:   PDF Manual  

GPL (>= 2) license

Imports class, cluster, conclust, corrplot, e1071, factoextra, FactoMineR, ggplot2, grid, jpeg, MASS, mclust, mda, mmand, nnet, png, randomForest, reshape, sp, stringi, stringr, tools

Depends on tcltk, tcltk2, tkrplot

System requirements: XQuartz (on OSX)

See at CRAN