SOMDisco is an R package intended to address several advances in SOM learning and analysis that are currently missing in currently available SOM packages for R (som, kohonen, and popsom). The main contributions of SOMDisco are:

• Integration of DeSieno's Conscience-SOM modifications to Kohonen's original algorithm to attempt maximum entropy SOM learning
• Fast and efficient C++ implementation of CSOM training (based on Rcpp and RcppArmadillo)
• Optional parallel SOM training and recall (as applicable, via RcppParallel)
• Computation of the CADJ matrix, which is a weighted topological adjacency of SOM prototypes helpful in cluster discovery
• The CONNvis visualization (requires the TopoRNet R package) which represents the topological information in CADJ on the SOM lattice
• Other advanced SOM visualizations (the mU-matrix, propagation of discrete and continuous values on the lattice)

devtools::install_github("somdisco/SOMDisco")

See the SOMDisco homepage for more information.