Man pages for som.nn
Topological k-NN Classifier Based on Self-Organising Maps

dist.fun.bubble	Bubble distance functions for topological k-NN classifier
dist.fun.inverse	Inverse exponential distance functions for topological k-NN...
dist.fun.linear	Linear distance functions for topological k-NN classifier
dist.fun.tricubic	Tricubic distance functions for topological k-NN classifier
dist.torus	Torus distance matrix
hexbinpie	Plots the hexagonals and pi charts. Adapted code from package...
initialize-methods	Constructor of SOMnn Class
make.codes.grid	Makes a data.frame with codes coordinates
makehexbinplot	makes the actual heagonal plot. Adapted code from package...
norm.linear	Linear normalisation
norm.softmax	Softmax normalisation
plot-methods	Plot method for S4 class 'SOMnn'
plot.predictions	Plots predicted samples as points into a plotted som.
predict-methods	predict method for S4 class 'SOMnn'
round.probabilities	Advanced rounding of vectors
SOMnn-class	An S4 class to hold a model for the topological classifier...
som.nn.continue	Continue hexagonal som training
som.nn.do.train	Work hourse for hexagonal som training
som.nn.export.kohonen	Export a som.nn model as object of type 'kohonen'
som.nn.export.som	Export a som.nn model as object of type 'SOM'
som.nn.max.row	Special version of maximum finder for SOMnn
som.nn-package	Topological k-NN Classifier Based on Self-Organising Maps
som.nn.round.votes	Rounds a dataframe with vectors of votes for SOMnn
som.nn.run.kernel	calls the specified kernel for som training.
som.nn.set	Set parameters for k-NN-like classifier in som.nn model
som.nn.som.experimental	Work hourse for som training.
som.nn.som.gaussian	Gaussian kernel for som training.
som.nn.som.internal	Work hourse for som training.
som.nn.train	Hexagonal som training
som.nn.validate	Predict class labels for a validation dataset
som.nn.visual	Mapping function for SOMnn
som.nn.visual.one	Maps one vector to the SOM